Philippa Kaur

1.Berge, J. et al. Artificial light during the polar night disrupts Arctic fish and zooplankton behaviour down to 200 m depth. Commun. Biol. 3, 102. https://doi.org/10.1038/s42003-020-0807-6 (2020).Article 
PubMed 
PubMed Central 

Google Scholar 
2.Davies, T. W., McKee, D., Fishwick, J., Tidau, S. & Smyth, T. Biologically important artificial light at night on the seafloor. Sci. Rep. 10, 12545. https://doi.org/10.1038/s41598-020-69461-6 (2020).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
3.Ludvigsen, M. et al. Use of an autonomous surface vehicle reveals small-scale diel vertical migrations of zooplankton and susceptibility to light pollution under low solar irradiance. Sci. Adv. 4, eaap9887. https://doi.org/10.1126/sciadv.aap9887 (2018).ADS 
Article 
PubMed 
PubMed Central 

Google Scholar 
4.Utne-Palm, A. C., Breen, M., Løkkeborg, S. & Humborstad, O. B. Behavioural responses of krill and cod to artificial light in laboratory experiments. PLoS One https://doi.org/10.1371/journal.pone.0190918 (2018).Article 
PubMed 
PubMed Central 

Google Scholar 
5.Marchesan, M., Spoto, M., Verginella, L. & Ferrero, E. A. Behavioural effects of artificial light on fish species of commercial interest. Fish. Res. 73, 171–185. https://doi.org/10.1016/j.fishres.2004.12.009 (2005).Article 

Google Scholar 
6.Stickney, A. P. Factors influencing the attraction of Atlantic Herring. Fish. Bull. 68, 73–85 (1969).
Google Scholar 
7.Nguyen, K. Q. et al. Application of luminescent netting in traps to improve the catchability of the snow crab Chionoecetes opilio. Mar. Coast. Fish. 11, 295–304. https://doi.org/10.1002/mcf2.10084 (2019).Article 

Google Scholar 
8.Wiebe, P. H. et al. Using a high-powered strobe light to increase the catch of Antarctic krill. Mar. Biol. 144, 493–502. https://doi.org/10.1007/s00227-003-1228-z (2004).Article 

Google Scholar 
9.Nguyen, T. T. et al. Artificial light pollution increases the sensitivity of tropical zooplankton to extreme warming. Environ. Technol. Innov. 20, 101179. https://doi.org/10.1016/j.eti.2020.101179 (2020).Article 

Google Scholar 
10.Kaartvedt, S., Røstad, A., Opdal, A. F. & Aksnes, D. L. Herding mesopelagic fish by light. Mar. Ecol. Prog. Ser. 625, 225–231 (2019).ADS 
Article 

Google Scholar 
11.Underwood, M. J., Utne Palm, A. C., Øvredal, J. T. & Bjordal, Å. The response of mesopelagic organisms to artificial lights. Aquac. Fish. https://doi.org/10.1016/j.aaf.2020.05.002 (2020).Article 

Google Scholar 
12.Peña, M., Cabrera-Gámez, J. & Domínguez-Brito, A. C. Multi-frequency and light-avoiding characteristics of deep acoustic layers in the North Atlantic. Mar. Environ. Res. 154, 104842. https://doi.org/10.1016/j.marenvres.2019.104842 (2020).CAS 
Article 
PubMed 

Google Scholar 
13.Ryer, C. H., Stoner, A. W., Iseri, P. J. & Spencer, M. L. Effects of simulated underwater vehicle lighting on fish behavior. Mar. Ecol. Prog. Ser. 391, 97–106 (2009).ADS 
Article 

Google Scholar 
14.Bicknell, A. W. J., Godley, B. J., Sheehan, E. V., Votier, S. C. & Witt, M. J. Camera technology for monitoring marine biodiversity and human impact. Front. Ecol. Environ. 14, 424–432. https://doi.org/10.1002/fee.1322 (2016).Article 

Google Scholar 
15.Picheral, M. et al. The Underwater Vision Profiler 5: An advanced instrument for high spatial resolution studies of particle size spectra and zooplankton. Limnol. Oceanogr. Meth. 8, 462–547. https://doi.org/10.4319/lom.2010.8.462 (2010).Article 

Google Scholar 
16.Herman, A. W. & Harvey, M. Application of normalized biomass size spectra to laser optical plankton counter net intercomparisons of zooplankton distributions. J. Geophys. Res. Oceans. https://doi.org/10.1029/2005JC002948 (2006).Article 

Google Scholar 
17.Basedow, S. L., Tande, K. S., Norrbin, M. F. & Kristiansen, S. A. Capturing quantitative zooplankton information in the sea: Performance test of laser optical plankton counter and video plankton recorder in a Calanus finmarchicus dominated summer situation. Prog. Oceanogr. 108, 72–80. https://doi.org/10.1016/j.pocean.2012.10.005 (2013).ADS 
Article 

Google Scholar 
18.Sainmont, J. et al. Inter- and intra-specific diurnal habitat selection of zooplankton during the spring bloom observed by Video Plankton Recorder. Mar. Biol. 161, 1931–1941. https://doi.org/10.1007/s00227-014-2475-x (2014).Article 

Google Scholar 
19.Schulz, J. et al. Imaging of plankton specimens with the lightframe on-sight key species investigation (LOKI) system. J. Eur. Opt. Soc. 5, 10017s (2010).Article 

Google Scholar 
20.Schmid, M. S., Aubry, C., Grigor, J. & Fortier, L. The LOKI underwater imaging system and an automatic identification model for the detection of zooplankton taxa in the Arctic Ocean. Meth. Oceanogr. 15–16, 129–160. https://doi.org/10.1016/j.mio.2016.03.003 (2016).Article 

Google Scholar 
21.Williams, K., Rooper, C. N. & Towler, R. Use of stereo camera systems for assessment of rockfish abundance in untrawlable areas and for recording pollock behavior during midwater trawls. Fish. Bull. 108, 352–362 (2010).
Google Scholar 
22.Boldt, J. L., Williams, K., Rooper, C. N., Towler, R. H. & Gauthier, S. Development of stereo camera methodologies to improve pelagic fish biomass estimates and inform ecosystem management in marine waters. Fish. Res. 198, 66–77. https://doi.org/10.1016/j.fishres.2017.10.013 (2018).Article 

Google Scholar 
23.Mallet, D. & Pelletier, D. Underwater video techniques for observing coastal marine biodiversity: A review of sixty years of publications (1952–2012). Fish. Res. 154, 44–62. https://doi.org/10.1016/j.fishres.2014.01.019 (2014).Article 

Google Scholar 
24.Easton, R. R., Heppell, S. S. & Hannah, R. W. Quantification of habitat and community relationships among nearshore temperate fishes through analysis of drop camera video. Mar. Coast. Fish. 7, 87–102. https://doi.org/10.1080/19425120.2015.1007184 (2015).Article 

Google Scholar 
25.McLean, D. L. et al. Using industry ROV videos to assess fish associations with subsea pipelines. Cont. Shelf Res. 141, 76–97. https://doi.org/10.1016/j.csr.2017.05.006 (2017).ADS 
Article 

Google Scholar 
26.Devine, B. M., Wheeland, L. J., de Moura Neves, B. & Fisher, J. A. D. Baited remote underwater video estimates of benthic fish and invertebrate diversity within the eastern Canadian Arctic. Polar Biol. 42, 1323–1341. https://doi.org/10.1007/s00300-019-02520-5 (2019).Article 

Google Scholar 
27.Trenkel, V. M., Lorance, P. & Mahévas, S. Do visual transects provide true population density estimates for deepwater fish?. ICES J. Mar. Sci. 61, 1050–1056. https://doi.org/10.1016/j.icesjms.2004.06.002 (2004).Article 

Google Scholar 
28.Widder, E. A., Robison, B. H., Reisenbichler, K. R. & Haddock, S. H. D. Using red light for in situ observations of deep-sea fishes. Deep-Sea Res. Part I(52), 2077–2085. https://doi.org/10.1016/j.dsr.2005.06.007 (2005).ADS 
Article 

Google Scholar 
29.Benoit-Bird, K. J., Moline, M. A., Schofield, O. M., Robbins, I. C. & Waluk, C. M. Zooplankton avoidance of a profiled open-path fluorometer. J. Plankton Res. 32, 1413–1419. https://doi.org/10.1093/plankt/fbq053 (2010).Article 

Google Scholar 
30.Doya, C. et al. Diel behavioral rhythms in sablefish (Anoplopoma fimbria) and other benthic species, as recorded by the Deep-sea cabled observatories in Barkley canyon (NEPTUNE-Canada). J. Mar. Syst. 130, 69–78. https://doi.org/10.1016/j.jmarsys.2013.04.003 (2014).Article 

Google Scholar 
31.Stoner, A. W., Ryer, C. H., Parker, S. J., Auster, P. J. & Wakefield, W. W. Evaluating the role of fish behavior in surveys conducted with underwater vehicles. Can. J. Fish. Aquat. Sci. 65, 1230–1243. https://doi.org/10.1139/f08-032 (2008).Article 

Google Scholar 
32.Rooper, C. N., Williams, K., De Robertis, A. & Tuttle, V. Effect of underwater lighting on observations of density and behavior of rockfish during camera surveys. Fish. Res. 172, 157–167. https://doi.org/10.1016/j.fishres.2015.07.012 (2015).Article 

Google Scholar 
33.Hop, H. et al. The marine ecosystem of Kongsfjorden, Svalbard. Polar Res. 21, 167–208 (2002).Article 

Google Scholar 
34.Bandara, K. et al. Seasonal vertical strategies in a high-Arctic coastal zooplankton community. Mar. Ecol. Prog. Ser. 555, 49–64 (2016).ADS 
Article 

Google Scholar 
35.Hop, H. et al. In The Ecosystem of Kongsfjorden, Svalbard (eds Hop, H. & Wiencke, C.) 229–300 (Springer International Publishing, 2019).Chapter 

Google Scholar 
36.Cusa, M., Berge, J. & Varpe, Ø. Seasonal shifts in feeding patterns: Individual and population realized specialization in a high Arctic fish. Ecol. Evol. 9, 11112–11121. https://doi.org/10.1002/ece3.5615 (2019).Article 
PubMed 
PubMed Central 

Google Scholar 
37.Sakshaug, E., Johnsen, G. & Volent, Z. In Ecosystem Barents Sea (eds Sakshaug, E. et al.) 117–138 (Tapir Academic Press, 2009).
Google Scholar 
38.Gordon, H. R. Can the Lambert–Beer law be applied to the diffuse attenuation coefficient of ocean water?. Limnol. Oceanogr. 34, 1389–1409. https://doi.org/10.4319/lo.1989.34.8.1389 (1989).ADS 
Article 

Google Scholar 
39.McKee, D., Cunningham, A. & Craig, S. Estimation of absorption and backscattering coefficients from in situ radiometric measurements: Theory and validation in case II waters. App. Opt. 42, 2804–2810. https://doi.org/10.1364/AO.42.002804 (2003).ADS 
Article 

Google Scholar 
40.Demer, D. A. et al. Calibration of acoustic instruments. ICES Cooperative Research Report No. 326. 133 (2015).41.Mackenzie, K. V. Nine-term equation for sound speed in the oceans. J. Acoust. Soc. Am. 70, 807 (1981).ADS 
Article 

Google Scholar 
42.François, R. E. & Garrison, G. R. Sound absorption based on ocean measurements. Part II: Boric acid contribution and equation for total absorption. J. Acoust. Soc. Am. 72, 1879–1890 (1982).ADS 
Article 

Google Scholar 
43.De Robertis, A. & Higginbottom, I. A post-processing technique to estimate the signal-to-noise ratio and remove echosounder background noise. ICES J. Mar. Sci. 64, 1282–1291. https://doi.org/10.1093/icesjms/fsm112 (2007).Article 

Google Scholar 
44.Ryan, T. E., Downie, R. A., Kloser, R. J. & Keith, G. Reducing bias due to noise and attenuation in open-ocean echo integration data. ICES J. Mar. Sci. 72, 2482–2493. https://doi.org/10.1093/icesjms/fsv121 (2015).Article 

Google Scholar 
45.Bates, D., Machler, M., Bolker, B. M. & Walker, S. C. Fitting linear mixed-effects models using lme4. J. Stat. Soft. 67, 1–48. https://doi.org/10.18637/jss.v067.i01 (2015).Article 

Google Scholar 
46.Bolker, B. M. et al. Generalized linear mixed models: A practical guide for ecology and evolution. TREE 24, 127–135. https://doi.org/10.1016/j.tree.2008.10.008 (2009).Article 
PubMed 

Google Scholar 
47.Berge, J. et al. Unexpected levels of biological activity during the polar night offer new perspectives on a warming Arctic. Curr. Biol. 25, 2555–2561. https://doi.org/10.1016/j.cub.2015.08.024 (2015).CAS 
Article 
PubMed 

Google Scholar 
48.Dalpadado, P. et al. Distribution and abundance of euphausiids and pelagic amphipods in Kongsfjorden, Isfjorden and Rijpfjorden (Svalbard) and changes in their relative importance as key prey in a warming marine ecosystem. Polar Biol. 39, 1765–1784. https://doi.org/10.1007/s00300-015-1874-x (2016).Article 

Google Scholar 
49.Geoffroy, M. et al. Increased occurrence of the jellyfish Periphylla periphylla in the European high Arctic. Polar Biol. 41, 2615–2619. https://doi.org/10.1007/s00300-018-2368-4 (2018).Article 

Google Scholar 
50.Jarms, G., Tiemann, H. & Båmstedt, U. Development and biology of Periphylla periphylla (Scyphozoa: Coronatae) in a Norwegian fjord. Mar. Biol. 141, 647–657. https://doi.org/10.1007/s00227-002-0858-x (2002).Article 

Google Scholar 
51.Pepin, P., Colbourne, E. & Maillet, G. Seasonal patterns in zooplankton community structure on the Newfoundland and Labrador Shelf. Prog. Oceanogr. 91, 273–285. https://doi.org/10.1016/j.pocean.2011.01.003 (2011).ADS 
Article 

Google Scholar 
52.Cohen, J. H. & Epifanio, C. E. In Developmental Biology and Larval Ecology, Ch. 12 (eds Anger, K. et al.) 332–359 (Oxford University Press, 2020).
Google Scholar 
53.Orr, M. H. Remote acoustic detection of zooplankton response to field processes, oceanographic instrumentation, and predators. Can. J. Fish. Aquat. Sci. 38, 1096–1105. https://doi.org/10.1139/f81-149 (1981).Article 

Google Scholar 
54.Farmer, D. D., Crawford, G. B. & Osborn, T. R. Temperature and velocity microstructure caused by swimming fish1. Limnol. Oceanogr. 32, 978–983. https://doi.org/10.4319/lo.1987.32.4.0978 (1987).ADS 
Article 

Google Scholar 
55.Koslow, J. A., Kloser, R. & Stanley, C. A. Avoidance of a camera system by a deepwater fish, the orange roughy (Hoplostethus atlanticus). Deep-Sea Res Part I 42, 233–244. https://doi.org/10.1016/0967-0637(95)93714-P (1995).Article 

Google Scholar 
56.Raymond, E. H. & Widder, E. A. Behavioral responses of two deep-sea fish species to red, far-red, and white light. Mar. Ecol. Prog. Ser. 350, 291–298 (2007).ADS 
Article 

Google Scholar 
57.Bassett, D. K. & Montgomery, J. C. Investigating nocturnal fish populations in situ using baited underwater video: With special reference to their olfactory capabilities. J. Exp. Mar. Biol. Ecol. 409, 194–199. https://doi.org/10.1016/j.jembe.2011.08.019 (2011).Article 

Google Scholar 
58.Brill, R., Magel, C., Davis, M., Hannah, R. & Rankin, P. Effects of rapid decompression and exposure to bright light on visual function in black rockfish (Sebastes melanops) and Pacific halibut (Hippoglossus stenolepis). Fish. Bull. 106, 427–437 (2008).
Google Scholar 
59.Turner, J. R., White, E. M., Collins, M. A., Partridge, J. C. & Douglas, R. H. Vision in lanternfish (Myctophidae): Adaptations for viewing bioluminescence in the deep-sea. Deep-Sea Res. Part I 56, 1003–1017. https://doi.org/10.1016/j.dsr.2009.01.007 (2009).CAS 
Article 

Google Scholar 
60.de Busserolles, F. & Marshall, N. J. Seeing in the deep-sea: Visual adaptations in lanternfishes. Philos. Trans. R Soc. Lond. B Biol. Sci. 372, 20160070. https://doi.org/10.1098/rstb.2016.0070 (2017).Article 
PubMed 
PubMed Central 

Google Scholar 
61.Valen, R., Edvardsen, R. B., Søviknes, A. M., Drivenes, Ø. & Helvik, J. V. Molecular evidence that only two opsin subfamilies, the blue light- (SWS2) and green light-sensitive (RH2), drive colour vision in Atlantic cod (Gadus morhua). PLoS One 9, e115436. https://doi.org/10.1371/journal.pone.0115436 (2015).ADS 
CAS 
Article 

Google Scholar 
62.Anthony, P. D. & Hawkins, A. D. Spectral sensitivity of the cod, Gadus morhua L. Mar. Behav. Physiol. 10, 145–166. https://doi.org/10.1080/10236248309378614 (1983).Article 

Google Scholar 
63.Govardovskii, V. I., Fyhrquist, N., Reuter, T., Kuzmin, D. G. & Donner, K. In search of the visual pigment template. Vis. Neurosci. 17, 509–528. https://doi.org/10.1017/s0952523800174036 (2000).CAS 
Article 
PubMed 

Google Scholar 
64.Frank, T. M. & Widder, E. A. Comparative study of the spectral sensitivities of mesopelagic crustaceans. J. Comp. Physiol. A 185, 255–265. https://doi.org/10.1007/s003590050385 (1999).Article 

Google Scholar 
65.Båtnes, A. S., Miljeteig, C., Berge, J., Greenacre, M. & Johnsen, G. Quantifying the light sensitivity of Calanus spp. during the polar night: Potential for orchestrated migrations conducted by ambient light from the sun, moon, or aurora borealis?. Polar Biol. 38, 1–15. https://doi.org/10.1007/s00300-013-1415-4 (2015).Article 

Google Scholar 
66.Cohen, J. H. et al. Is ambient light during the high Arctic polar night sufficient to act as a visual cue for zooplankton?. PLoS ONE https://doi.org/10.1371/journal.pone.0126247 (2015).Article 
PubMed 
PubMed Central 

Google Scholar 
67.Jinks, R. N. et al. Adaptive visual metamorphosis in a deep-sea hydrothermal vent crab. Nature 420, 68–70. https://doi.org/10.1038/nature01144 (2002).ADS 
CAS 
Article 
PubMed 

Google Scholar 
68.Aguzzi, J. et al. The potential of video imagery from worldwide cabled observatory networks to provide information supporting fish-stock and biodiversity assessment. ICES J. Mar. Sci. https://doi.org/10.1093/icesjms/fsaa169 (2020).Article 

Google Scholar  More

1.Goordial J, Davila A, Lacelle D, Pollard W, Marinova MM, Greer CW, et al. Nearing the cold-arid limits of microbial life in permafrost of an upper dry valley, Antarctica. ISME J. 2016;10:1613.PubMed 
PubMed Central 
Article 

Google Scholar 
2.Mykytczuk NC, Foote SJ, Omelon CR, Southam G, Greer CW, Whyte LG. Bacterial growth at −15 C; molecular insights from the permafrost bacterium Planococcus halocryophilus Or1. ISME J. 2013;7:1211.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
3.Margesin R, Miteva V. Diversity and ecology of psychrophilic microorganisms. Res Microbiol. 2011;162:346–61.PubMed 
Article 

Google Scholar 
4.De Maayer P, Anderson D, Cary C, Cowan DA. Some like it cold: understanding the survival strategies of psychrophiles. EMBO Rep. 2014;15:508–17.PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
5.Hassan N, Rafiq M, Hayat M, Shah AA, Hasan F. Psychrophilic and psychrotrophic fungi: a comprehensive review. Rev Environ Sci Bio. 2016;15:147–72.Article 

Google Scholar 
6.Christner BC, Mosley‐Thompson E, Thompson LG, Reeve JN. Bacterial recovery from ancient glacial ice. Environ Microbiol. 2003;5:433–6.CAS 
PubMed 
Article 

Google Scholar 
7.Raymond-Bouchard I, Goordial J, Zolotarov Y, Ronholm J, Stromvik M, Bakermans C, et al. Conserved genomic and amino acid traits of cold adaptation in subzero-growing Arctic permafrost bacteria. FEMS Microbiol Ecol. 2018;94:fiy023.Article 
CAS 

Google Scholar 
8.Raymond-Bouchard I, Tremblay J, Altshuler I, Greer CW, Whyte LG. Comparative transcriptomics of cold growth and adaptive features of a eury-and steno-psychrophile. Front Microbiol. 2018;9:1565.PubMed 
PubMed Central 
Article 

Google Scholar 
9.Buzzini P, Margesin R. Cold-adapted yeasts: a lesson from the cold and a challenge for the XXI century. In: Buzzini P, Margesin R, editors. Cold-adapted yeasts. Heidelberg: Springer; 2014. p. 3–22.Chapter 

Google Scholar 
10.Altshuler I, Goordial J, Whyte LG. Microbial life in permafrost. In: Margesin R, editor. Psychrophiles: from biodiversity to biotechnology. 2nd edn. Cham: Springer; 2017. p. 153–79.Chapter 

Google Scholar 
11.Gilichinsky D, Wilson G, Friedmann E, McKay C, Sletten R, Rivkina E, et al. Microbial populations in Antarctic permafrost: biodiversity, state, age, and implication for astrobiology. Astrobiology. 2007;7:275–311.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
12.de Menezes GCA, Porto BA, Amorim SS, Zani CL, de Almeida Alves TM, Junior PAS, et al. Fungi in glacial ice of Antarctica: diversity, distribution and bioprospecting of bioactive compounds. Extremophiles. 2020;24:367–76.PubMed 
Article 
PubMed Central 

Google Scholar 
13.Zhang T, Wang N, Yu L. Soil fungal community composition differs significantly among the Antarctic, Arctic, and Tibetan Plateau. Extremophiles. 2020;24:821–9.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
14.Coleine C, Zucconi L, Onofri S, Pombubpa N, Stajich JE, Selbmann L. Sun exposure shapes functional grouping of fungi in cryptoendolithic Antarctic communities. Life. 2018;8:19.PubMed Central 
Article 
CAS 

Google Scholar 
15.Gunde-Cimerman N, Zalar P, de Hoog S, Plemenitaš A. Hypersaline waters in salterns–natural ecological niches for halophilic black yeasts. FEMS Microbiol Ecol. 2000;32:235–40.CAS 

Google Scholar 
16.Perini L, Gostinčar C, Anesio AM, Williamson C, Tranter M, Gunde-Cimerman N. Darkening of the Greenland Ice Sheet: fungal abundance and diversity are associated with algal bloom. Front Microbiol. 2019;10:557.PubMed 
PubMed Central 
Article 

Google Scholar 
17.Tojo M, Newsham KK. Snow moulds in polar environments. Fungal Ecol. 2012;5:395–402.Article 

Google Scholar 
18.Rosa LH, Vaz AB, Caligiorne RB, Campolina S, Rosa CA. Endophytic fungi associated with the Antarctic grass Deschampsia antarctica Desv.(Poaceae). Polar Biol. 2009;32:161–7.Article 

Google Scholar 
19.Gianoli E, Inostroza P, Zúñiga-Feest A, Reyes-Díaz M, Cavieres LA, Bravo LA, et al. Ecotypic differentiation in morphology and cold resistance in populations of Colobanthus quitensis (Caryophyllaceae) from the Andes of central Chile and the maritime Antarctic. Arct Antarct Alp Res. 2004;36:484–9.Article 

Google Scholar 
20.Duncan SM, Farrell RL, Thwaites JM, Held BW, Arenz BE, Jurgens JA, et al. Endoglucanase‐producing fungi isolated from Cape Evans historic expedition hut on Ross Island, Antarctica. Environ Microbiol. 2006;8:1212–9.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
21.Starmer WT, Lachance M-A. Yeast ecology. In: Kurtzman CP, Fell JW, Boekhout T, eds. The yeasts. 5ft ed. London: Elsevier; 2011. p. 65–83.Chapter 

Google Scholar 
22.Shivaji S, Prasad G. Antarctic yeasts: biodiversity and potential applications. In: Satyanarayana T, Kunze G, editors. Yeast biotechnology: diversity and applications. New Delhi: Springer; 2009. p. 3–18.Chapter 

Google Scholar 
23.Gunde-Cimerman N, Plemenitaš A, Buzzini P. Changes in lipids composition and fluidity of yeast plasma membrane as response to cold. In: Buzzini P, Margesin R, editors. Cold-adapted yeasts. Heidelberg: Springer; 2014. p. 225–42.Chapter 

Google Scholar 
24.Goordial J, Raymond-Bouchard I, Riley R, Ronholm J, Shapiro N, Woyke T, et al. Improved high-quality draft genome sequence of the eurypsychrophile Rhodotorula sp. JG1b, isolated from permafrost in the hyperarid upper-elevation mcmurdo dry valleys, Antarctica. Genome Announc. 2016;4:e00069–16.PubMed 
PubMed Central 
Article 

Google Scholar 
25.Yen H-W, Liao Y-T, Liu YX. Cultivation of oleaginous Rhodotorula mucilaginosa in airlift bioreactor by using seawater. J Biosci Bioeng. 2016;121:209–12.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
26.Buzzini P, Turk M, Perini L, Turchetti B, Gunde-Cimerman N. Yeasts in polar and subpolar habitats. In: Buzzini P, Lachance M-A, Yurkov A, editors. Yeasts in natural ecosystems: diversity. Cham: Springer; 2017. p. 331–65.Chapter 

Google Scholar 
27.Margesin R, Fonteyne P-A, Schinner F, Sampaio JP. Rhodotorula psychrophila sp. nov., Rhodotorula psychrophenolica sp. nov. and Rhodotorula glacialis sp. nov., novel psychrophilic basidiomycetous yeast species isolated from alpine environments. Int J Syst Evol Micr. 2007;57:2179–84.CAS 
Article 

Google Scholar 
28.Sabri A, Jacques P, Weekers F, Bare G, Hiligsmann S, Moussaif M, et al. Effect of temperature on growth of psychrophilic and psychrotrophic members of Rhodotorula aurantiaca. In: Walt DR, editor. Applied biochemistry and biotechnology. New York: Springer Science+Business Media; 2000. p. 391–9.
Google Scholar 
29.Marchant DR, Head JW III. Antarctic dry valleys: microclimate zonation, variable geomorphic processes, and implications for assessing climate change on Mars. Icarus 2007;192:187–222.Article 

Google Scholar 
30.Kurtzman C, Fell JW, Boekhout T, editors. The yeasts: a taxonomic study. 5ft ed. London: Elsevier; 2011.
Google Scholar 
31.Kornerup A, Wanscher JH, editors. Methuen handbook of colour. 2nd ed. London: Methuen and Co.; 1967.
Google Scholar 
32.Xing W, Yin M, Lv Q, Hu Y, Liu C, Zhang J. Oxygen solubility, diffusion coefficient, and solution viscosity. In: Xing W, Yin G, Zhang J, editors. Rotating electrode methods and oxygen reduction electrocatalysts. London: Elsevier; 2014. p. 1–31.
Google Scholar 
33.Viti C, Decorosi F, Marchi E, Galardini M, Giovannetti L. High-throughput phenomics. In: Mengoni A, Galardini M, Fondi M, editors. Bacterial pangenomics. Methods and protocols. New York: Springer; 2015. p. 99–123.Chapter 

Google Scholar 
34.Rico A, Preston GM. Pseudomonas syringae pv. tomato DC3000 uses constitutive and apoplast-induced nutrient assimilation pathways to catabolize nutrients that are abundant in the tomato apoplast. Mol Plant Microbe. 2008;21:269–82.CAS 
Article 

Google Scholar 
35.Patro R, Duggal G, Love MI, Irizarry RA, Kingsford C. Salmon provides fast and bias-aware quantification of transcript expression. Nat Methods. 2017;14:417.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
36.Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014;15:550.PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
37.Kanehisa M, Sato Y, Morishima K. BlastKOALA and GhostKOALA: KEGG tools for functional characterization of genome and metagenome sequences. J Mol Biol. 2016;428:726–31.CAS 
PubMed 
Article 

Google Scholar 
38.Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ. Basic local alignment search tool. J Mol Biol. 1990;215:403–10.CAS 
Article 

Google Scholar 
39.Krüger J, Rehmsmeier M. RNAhybrid: microRNA target prediction easy, fast and flexible. Nucleic Acids Res. 2006;34:W451–54.PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
40.Rehmsmeier M, Steffen P, Höchsmann M, Giegerich R. Fast and effective prediction of microRNA/target duplexes. RNA. 2004;10:1507–17.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
41.Greetham D. Phenotype microarray technology and its application in industrial biotechnology. Biotechnol Lett. 2014;36:1153–60.CAS 
PubMed 
Article 

Google Scholar 
42.Bochner BR. Global phenotypic characterization of bacteria. FEMS Microbiol Rev. 2008;33:191–205.PubMed 
Article 
CAS 

Google Scholar 
43.Maldonado F, Packard T, Gómez M. Understanding tetrazolium reduction and the importance of substrates in measuring respiratory electron transport activity. J Exp Mar Biol Ecol. 2012;434:110–8.Article 
CAS 

Google Scholar 
44.Barclay BJ, DeHaan CL, Hennig UG, Iavorovska O, von Borstel RW, Von, et al. A rapid assay for mitochondrial DNA damage and respiratory chain inhibition in the yeast Saccharomyces cerevisiae. Environ Mol Mutagen. 2001;38:153–8.CAS 
PubMed 
Article 

Google Scholar 
45.Jenkins CL, Lawrence SJ, Kennedy AI, Thurston P, Hodgson JA, Smart KA. Incidence and formation of petite mutants in lager brewing yeast Saccharomyces cerevisiae (syn. S. pastorianus) populations. J Am Soc Brew Chem. 2009;67:72–80.CAS 

Google Scholar 
46.Glab N, Wise R, Pring D, Jacq C, Slonimski P. Expression in Saccharomyces cerevisiae of a gene associated with cytoplasmic male sterility from maize: respiratory dysfunction and uncoupling of yeast mitochondria. Mol Gen Genet. 1990;223:24–32.CAS 
PubMed 
Article 

Google Scholar 
47.Goldring ES, Grossman LI, Krupnick D, Cryer DR, Marmur J. The petite mutation in yeast: loss of mitochondrial deoxyribonucleic acid during induction of petites with ethidium bromide. J Mol Biol. 1970;52:323–35.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
48.Vogel C, Marcotte EM. Insights into the regulation of protein abundance from proteomic and transcriptomic analyses. Nat Rev Genet. 2012;13:227–32.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
49.Pinatel E, Peano C. RNA sequencing and analysis in microorganisms for metabolic network reconstruction. In: Fondi M, editor. Metabolic network reconstruction and modeling. Methods and protocols. New York: Springer; 2018. p. 239–65.Chapter 

Google Scholar 
50.Raymond‐Bouchard I, Chourey K, Altshuler I, Iyer R, Hettich RL, Whyte LG. Mechanisms of subzero growth in the cryophile Planococcus halocryophilus determined through proteomic analysis. Environ Microbiol. 2017;19:4460–79.PubMed 
Article 
CAS 

Google Scholar 
51.Bhuiyan M, Tucker D, Watson K. Gas chromatography–mass spectrometry analysis of fatty acid profiles of Antarctic and non-Antarctic yeasts. Anton Leeuw. 2014;106:381–9.CAS 
Article 

Google Scholar 
52.López-Malo M, Chiva R, Rozes N, Guillamon JM. Phenotypic analysis of mutant and overexpressing strains of lipid metabolism genes in Saccharomyces cerevisiae: implication in growth at low temperatures. Int J Food Microbiol. 2013;162:26–36.PubMed 
Article 
CAS 

Google Scholar 
53.Rossi M, Buzzini P, Cordisco L, Amaretti A, Sala M, Raimondi S, et al. Growth, lipid accumulation, and fatty acid composition in obligate psychrophilic, facultative psychrophilic, and mesophilic yeasts. FEMS Microbiol Ecol. 2009;69:363–72.CAS 
PubMed 
Article 

Google Scholar 
54.Contreras G, Barahona S, Sepúlveda D, Baeza M, Cifuentes V, Alcaíno J. Identification and analysis of metabolite production with biotechnological potential in Xanthophyllomyces dendrorhous isolates. World J Micro Biot. 2015;31:517–26.CAS 
Article 

Google Scholar 
55.Libkind D, Arts M, Van Broock M. Fatty acid composition of cold-adapted carotenogenic basidiomycetous yeasts. Rev Argent Microbiol. 2008;40:193–7.CAS 
PubMed 

Google Scholar 
56.Thomas-Hall S, Watson K. Cryptococcus nyarrowii sp. nov., a basidiomycetous yeast from Antarctica. Int J Syst Evol Micr. 2002;52:1033–8.CAS 

Google Scholar 
57.López-Malo M, García-Ríos E, Chiva R, Guillamon JM. Functional analysis of lipid metabolism genes in wine yeasts during alcoholic fermentation at low temperature. Micro Cell. 2014;1:365.Article 
CAS 

Google Scholar 
58.Tai SL, Daran-Lapujade P, Walsh MC, Pronk JT, Daran J-M. Acclimation of Saccharomyces cerevisiae to low temperature: a chemostat-based transcriptome analysis. Mol Biol Cell. 2007;18:5100–12.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
59.Mao C, Wadleigh M, Jenkins GM, Hannun YA, Obeid LM. Identification and characterization of Saccharomyces cerevisiae dihydrosphingosine-1-phosphate phosphatase. J Biol Chem. 1997;272:28690–4.CAS 
PubMed 
Article 

Google Scholar 
60.Mata-Gómez LC, Montañez JC, Méndez-Zavala A, Aguilar CN. Biotechnological production of carotenoids by yeasts: an overview. Micro Cell Fact. 2014;13:12.Article 
CAS 

Google Scholar 
61.Moliné M, Flores MR, Libkind D. del Carmen Diéguez M, Farías ME, van Broock M. Photoprotection by carotenoid pigments in the yeast Rhodotorula mucilaginosa: the role of torularhodin. Photoch Photobio Sci. 2010;9:1145–51.Article 
CAS 

Google Scholar 
62.Liu GY, Nizet V. Color me bad: microbial pigments as virulence factors. Trends Microbiol. 2009;17:406–13.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
63.Rodrigues DF, Tiedje JM. Coping with our cold planet. Appl Environ Micro. 2008;74:1677–86.CAS 
Article 

Google Scholar 
64.Villarreal P, Carrasco M, Barahona S, Alcaíno J, Cifuentes V, Baeza M. Tolerance to ultraviolet radiation of psychrotolerant yeasts and analysis of their carotenoid, mycosporine, and ergosterol content. Curr Microbiol. 2016;72:94–101.CAS 
PubMed 
Article 

Google Scholar 
65.Moliné M, Libkind D, del Carmen DiéguezM, van Broock M. Photoprotective role of carotenoids in yeasts: response to UV-B of pigmented and naturally-occurring albino strains. J Photoch Photobio B 2009;95:156–61.Article 
CAS 

Google Scholar 
66.Huang G-T, Ma S-L, Bai L-P, Zhang L, Ma H, Jia P, et al. Signal transduction during cold, salt, and drought stresses in plants. Mol Biol Rep. 2012;39:969–87.PubMed 
Article 
CAS 

Google Scholar 
67.Heino P, Palva ET. Signal transduction in plant cold acclimation. In: Hirt H, Shinozaki K, editors. Plant responses to abiotic stress. Berlin: Springer; 2003. p. 151–86.Chapter 

Google Scholar 
68.Storey KB, Storey JM. Signal transduction and gene expression in the regulation of natural freezing survival. In: Storey KB, Storey JM, editors. Protein adaptations and signal transduction. London: Elsevier; 2001. p. 1–19.
Google Scholar 
69.Li W-H, Yang J, Gu X. Expression divergence between duplicate genes. Trends Genet. 2005;21:602–7.PubMed 
Article 
CAS 

Google Scholar 
70.Vollmers J, Voget S, Dietrich S, Gollnow K, Smits M, Meyer K, et al. Poles apart: arctic and Antarctic Octadecabacter strains share high genome plasticity and a new type of xanthorhodopsin. Plos One. 2013;8:e63422.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
71.Wagner A. Asymmetric functional divergence of duplicate genes in yeast. Mol Biol Evol. 2002;19:1760–8.CAS 
PubMed 
Article 

Google Scholar 
72.Varki A, Gagneux P. Biological functions of glycans. In: Varki A, Cummings RD, Esko JD, Stanley P, Hart GW, Aebi M, et al. editors. Essentials of glycobiology. 3rd ed. Cold Spring Harbor: Cold Spring Harbor Laboratory Press; 2017.
Google Scholar 
73.Colley K, Varki A, Kinoshita T. Cellular organization of glycosylation. In: Varki A, Cummings RD, Esko JD, Stanley P, Hart GW, Aebi M, et al. editors. Essentials of glycobiology. 3rd ed. Cold Spring Harbor: Cold Spring Harbor Laboratory Press; 2017.
Google Scholar 
74.Pavlova K, Panchev I, Hristozova T. Physico-chemical characterization of exomannan from Rhodotorula acheniorum MC. World J Micro Biot. 2005;21:279–83.CAS 
Article 

Google Scholar 
75.Cho DH, Chae HJ, Kim EY. Synthesis and characterization of a novel extracellular polysaccharide by Rhodotorula glutinis. Appl Biochem Biotech. 2001;95:183–93.CAS 
Article 

Google Scholar 
76.Flemming HC, Neu TR, Wingender J. The perfect slime. Microbial extracellular polymeric substances (EPS). London: IWA Publishing; 2016.Book 

Google Scholar 
77.Nichols WW, Evans MJ, Slack MP, Walmsley HL. The penetration of antibiotics into aggregates of mucoid and non-mucoid Pseudomonas aeruginosa. Microbiology. 1989;135:1291–303.CAS 
Article 

Google Scholar 
78.Selbmann L, Onofri S, Fenice M, Federici F, Petruccioli M. Production and structural characterization of the exopolysaccharide of the Antarctic fungus Phoma herbarum CCFEE 5080. Res Microbiol. 2002;153:585–92.CAS 
PubMed 
Article 

Google Scholar 
79.Rini JM, Esko JD. Glycosyltransferases and glycan-processing enzymes. In: Varki A, Cummings RD, Esko JD, Stanley P, Hart GW, Aebi M, et al. editors. Essentials of glycobiology. 3rd ed. Cold Spring Harbor: Cold Spring Harbor Laboratory Press; 2017.
Google Scholar 
80.Strassburg K, Walther D, Takahashi H, Kanaya S, Kopka J. Dynamic transcriptional and metabolic responses in yeast adapting to temperature stress. Omics. 2010;14:249–59.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
81.Becerra M, Lombardia L, Gonzalez-Siso M, Rodriguez-Belmonte E, Hauser N, Cerdán M. Genome-wide analysis of the yeast transcriptome upon heat and cold shock. Int J Genomics. 2003;4:366–75.CAS 

Google Scholar 
82.Homma T, Iwahashi H, Komatsu Y. Yeast gene expression during growth at low temperature. Cryobiology. 2003;46:230–7.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
83.Sahara T, Goda T, Ohgiya S. Comprehensive expression analysis of time-dependent genetic responses in yeast cells to low temperature. J Biol Chem. 2002;277:50015–21.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
84.Schade B, Jansen G, Whiteway M, Entian KD, Thomas DY. Cold adaptation in budding yeast. Mol Biol Cell. 2004;15:5492–502.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
85.Mikami K, Kanesaki Y, Suzuki I, Murata N. The histidine kinase Hik33 perceives osmotic stress and cold stress in Synechocystis sp. PCC 6803. Mol Microbiol. 2002;46:905–15.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
86.Tsuji M. Cold-stress responses in the Antarctic basidiomycetous yeast Mrakia blollopis. R Soc Open Sci. 2016;3:160106.PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
87.Sarkar D, Bhowmik PC, Kwon Y-I, Shetty K. Clonal response to cold tolerance in creeping bentgrass and role of proline-associated pentose phosphate pathway. Bioresour Technol. 2009;100:5332–9.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
88.Bura R, Vajzovic A, Doty SL. Novel endophytic yeast Rhodotorula mucilaginosa strain PTD3 I: production of xylitol and ethanol. J Ind Microbiol Biot. 2012;39:1003–11.CAS 
Article 

Google Scholar 
89.da Silva TL, Feijão D, Roseiro JC, Reis A. Monitoring Rhodotorula glutinis CCMI 145 physiological response and oil production growing on xylose and glucose using multi-parameter flow cytometry. Bioresour Technol. 2011;102:2998–3006.PubMed 
Article 
CAS 

Google Scholar 
90.Johansson B, Hahn-Hägerdal B. The non-oxidative pentose phosphate pathway controls the fermentation rate of xylulose but not of xylose in Saccharomyces cerevisiae TMB3001. FEMS Yeast Res. 2002;2:277–82.CAS 
PubMed 
PubMed Central 

Google Scholar 
91.Eliasson A, Boles E, Johansson B, Österberg M, Thevelein J, Spencer-Martins I, et al. Xylulose fermentation by mutant and wild-type strains of Zygosaccharomyces and Saccharomyces cerevisiae. Appl Microbiol Biot. 2000;53:376–82.CAS 
Article 

Google Scholar 
92.Mohamad N, Mustapa Kamal S, Mokhtar M. Xylitol biological production: a review of recent studies. Food Rev Int. 2015;31:74–89.CAS 
Article 

Google Scholar 
93.Shetty K, Wahlqvist M. A model for the role of the proline-linked pentose-phosphate pathway in phenolic phytochemical bio-synthesis and mechanism of action for human health and environmental applications. Asia Pac J Clin Nutr. 2004;13:1–24.CAS 
PubMed 
PubMed Central 

Google Scholar 
94.Fonseca P, Moreno R, Rojo F. Growth of Pseudomonas putida at low temperature: global transcriptomic and proteomic analyses. Environ Microbiol Rep. 2011;3:329–39.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
95.Rao R, Bhadra B, Shivaji S. Isolation and characterization of ethanol‐producing yeasts from fruits and tree barks. Lett Appl Microbiol. 2008;47:19–24.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
96.Kourkoutas Y, Komaitis M, Koutinas A, Kaliafas A, Kanellaki M, Marchant R, et al. Wine production using yeast immobilized on quince biocatalyst at temperatures between 30 and 0 C. Food Chem. 2003;82:353–60.CAS 
Article 

Google Scholar 
97.Kanellaki M, Koutinas AA. Low temperature fermentation of wine and beer by cold-adapted and immobilized yeast cells. In: Margesin R, Schinner F, editors. Biotechnological applications of cold-adapted organisms. Berlin: Springer; 1999. p. 117–45.Chapter 

Google Scholar 
98.Bakoyianis V, Kanellaki M, Kaliafas A, Koutinas A. Low-temperature wine making by immobilized cells on mineral kissiris. J Agr Food Chem. 1992;40:1293–6.CAS 
Article 

Google Scholar 
99.Tiwari R, Singh S, Shukla P, Nain L. Novel cold temperature active β-glucosidase from Pseudomonas lutea BG8 suitable for simultaneous saccharification and fermentation. RSC Adv. 2014;4:58108–15.CAS 
Article 

Google Scholar 
100.Tang W, Wang Y, Zhang J, Cai Y, He Z. Biosynthetic pathway of carotenoids in Rhodotorula and strategies for enhanced their production. J Microbiol Biotechn. 2019;29:507–17.CAS 
Article 

Google Scholar 
101.Steven B, Briggs G, McKay CP, Pollard WH, Greer CW, Whyte LG. Characterization of the microbial diversity in a permafrost sample from the Canadian high Arctic using culture-dependent and culture-independent methods. FEMS Microbiol Ecol. 2007;59:513–23.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
102.Dozmorov MG, Giles CB, Koelsch KA, Wren JD. Systematic classification of non-coding RNAs by epigenomic similarity. BMC Bioinforma. 2013;14:S2.Article 

Google Scholar 
103.Sunkar R, Li Y-F, Jagadeeswaran G. Functions of microRNAs in plant stress responses. Trends Plant Sci. 2012;17:196–203.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
104.Ambros V. MicroRNA pathways in flies and worms: growth, death, fat, stress, and timing. Cell. 2003;113:673–6.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
105.Lau SK, Chow W-N, Wong AY, Yeung JM, Bao J, Zhang N, et al. Identification of microRNA-like RNAs in mycelial and yeast phases of the thermal dimorphic fungus Penicillium marneffei. Plos Negl Trop D. 2013;7:e2398.Article 
CAS 

Google Scholar 
106.Zhou Q, Wang Z, Zhang J, Meng H, Huang B. Genome-wide identification and profiling of microRNA-like RNAs from Metarhizium anisopliae during development. Fungal Biol UK. 2012;116:1156–62.CAS 
Article 

Google Scholar 
107.Lambert M, Benmoussa A, Provost P. Small non-coding RNAs derived from eukaryotic ribosomal RNA. Noncoding RNA 2019;5:16.CAS 
PubMed Central 

Google Scholar 
108.Thompson DM, Lu C, Green PJ, Parker R. tRNA cleavage is a conserved response to oxidative stress in eukaryotes. RNA. 2008;14:2095–103.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
109.Gebetsberger J, Wyss L, Mleczko AM, Reuther J, Polacek N. A tRNA-derived fragment competes with mRNA for ribosome binding and regulates translation during stress. RNA Biol. 2017;14:1364–73.PubMed 
Article 
PubMed Central 

Google Scholar 
110.Bąkowska-Żywicka K, Kasprzyk M, Twardowski T. tRNA-derived short RNAs bind to Saccharomyces cerevisiae ribosomes in a stress-dependent manner and inhibit protein synthesis in vitro. FEMS Yeast Res. 2016;16:fow077.PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
111.McCool MA, Bryant CJ, Baserga SJ. MicroRNAs and long non-coding RNAs as novel regulators of ribosome biogenesis. Biochem Soc T. 2020;48:595–612.CAS 
Article 

Google Scholar 
112.Wei H, Zhou B, Zhang F, Tu Y, Hu Y, Zhang B, et al. Profiling and identification of small rDNA-derived RNAs and their potential biological functions. Plos One. 2013;8:e56842.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
113.Lee H-C, Chang S-S, Choudhary S, Aalto AP, Maiti M, Bamford DH, et al. qiRNA is a new type of small interfering RNA induced by DNA damage. Nature. 2009;459:274–7.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
114.Zhu C, Yan Q, Weng C, Hou X, Mao H, Liu D, et al. Erroneous ribosomal RNAs promote the generation of antisense ribosomal siRNA. P Natl Acad Sci USA. 2018;115:10082–7.CAS 
Article 

Google Scholar 
115.Zhou X, Chen X, Wang Y, Feng X, Guang S. A new layer of rRNA regulation by small interference RNAs and the nuclear RNAi pathway. RNA Biol. 2017;14:1492–8.PubMed 
PubMed Central 
Article 

Google Scholar 
116.Zhou X, Feng X, Mao H, Li M, Xu F, Hu K, et al. RdRP-synthesized antisense ribosomal siRNAs silence pre-rRNA via the nuclear RNAi pathway. Nat Struct Mol Biol. 2017;24:258.CAS 
PubMed 
Article 

Google Scholar  More

Profftia and Vallotia are related to free-living bacteria and fungus-associated endosymbiontsPrevious 16S rRNA-based phylogenetic analyses suggested an affiliation of Profftia with free-living gammaproteobacteria and a close phylogenetic relationship between Vallotia and betaproteobacterial endosymbionts of Rhizopus fungi [14]. Biased nucleotide composition and accelerated sequence evolution of endosymbiont genomes [2, 3] often result in inconsistent phylogenies and may cause grouping of unrelated taxa [55, 56]. Thus, to further investigate the phylogenetic relationships of the A. laricis/tardus symbionts, we used conserved marker genes for maximum likelihood and Bayesian phylogenetic analyses.Phylogenetic analysis of 45 single-copy proteins demonstrated that Profftia opens up a novel insect symbiont lineage most similar to Hafnia species and an isolate from the human gastrointestinal tract within the Hafniaceae, which has been recently designated as a distinct family within the Enterobacteriales [57] (Fig. S2). Hafnia strains are frequently identified in the gastrointestinal tract of humans and animals and were also found in insects [58, 59]. The phylogenomic placement of Profftia in our analysis is in agreement with previous 16S rRNA-based analyses [14].Vallotia formed a monophyletic group with Mycetohabitans endofungorum and M. rhizoxinica, endosymbionts of Rhizopus fungi within the Burkholderiaceae [60, 61] with strong support in phylogenetic analyses based on a concatenated set of 108 proteins (Figs. 1 and S3; previous taxonomic assignments of the fungus-associated symbionts were as Burkholderia/Paraburkholderia endofungorum and rhizoxinica, respectively). Interestingly, Vallotia and M. endofungorum appeared as well-supported sister taxa within this clade. This implies a closer phylogenetic relationship between Vallotia and M. endofungorum and a common origin of adelgid endosymbionts from within a clade of fungus-associated bacterial symbionts. Lengths of branches leading to the fungus-associated endosymbionts were similar to those of free-living bacteria in the data set; however, Vallotia had a remarkably longer branch marking a rapid rate of sequence evolution characteristic of obligate intracellular bacteria [2, 3]. M. endofungorum and M. rhizoxinica have been identified in the cytosol of the zygomycete Rhizopus microsporus, best known as the causative agent of rice seedling blight [61, 62]. The necrotrophic fungus secretes potent toxins, rhizoxin and rhizonin, which are produced by the endosymbionts. The bacterial partners are obligatory for their host as they tightly control its sporulation, while they benefit from host nutrients and spread with the fungal spores [63, 64]. Additionally, related bacterial strains have also been found in association with Rhizopus fungi worldwide in a diverse set of environments, including other plant species, soil, food, and even human tissues [65, 66].Fig. 1: Phylogenomic analysis showing the affiliation of the adelgid endosymbiont “Candidatus Vallotia tarda” and its closest relatives, the fungus-associated endosymbionts M. rhizoxinica and M. endofungorum within the Burkholderiaceae.Selected members of Oxalobacteraceae (Janthinobacterium agaricidamnosum [HG322949], Collimonas pratensis [CP013234], and Herbaspirillum seropedicae [CP011930]) were used as outgroup. Maximum likelihood and Bayesian analyses were performed based on a concatenated alignment of 108 proteins. Maximum likelihood tree is shown. SH-aLRT support (%) and ultrafast bootstrap support (%) values based on 1000 replicates, and Bayesian posterior probabilities are indicated on the internal nodes. Asterisks stand for a maximal support in each analysis (100%/1).Full size imageTaken together, phylogenomic analyses support that Profftia and Vallotia open up novel insect symbionts lineages most closely related to free-living bacteria within the Hafniaceae and a clade of fungus-associated endosymbionts within the Burkholderiaceae, respectively. Given the well-supported phylogenetic positioning of “Candidatus Vallotia tarda” nested within a clade formed by Mycetohabitans species, we propose the transfer of “Candidatus Vallotia tarda” to the Mycetohabitans genus, as “Candidatus Mycetohabitans vallotii” (a detailed proposal for the re-classification is given in the Supplementary Material).
Vallotia and Profftia are evolutionary young symbionts of adelgidsThe complete sequence of the Profftia chromosome had a length of 1,225,795 bp and a G + C content of 31.9% (Table 1). It encoded for 645 proteins, one copy of each rRNA, 35 transfer RNAs (tRNAs), and 10 non-coding RNAs (ncRNAs). It had tRNAs and amino acid charging potential for all 20 standard amino acids. However, protein-coding sequences (CDSs) made up only 52.4% of the genome, and 21 pseudogenes indicated an ongoing gene inactivation.Table 1 Genomic features of Profftia and Vallotia.Full size tableThe Vallotia chromosome had a length of 1,123,864 bp. It had a G + C content and a coding density of 42.9 and 64.9%, respectively. However, a 72,431-bp-long contig showed a characteristically lower G + C content (36.1%) and contained only 46.2% putative CDSs. This contig had identical repeats at its ends, and genome annotation revealed neighboring genes for a plasmid replication initiation protein, and ParA/ParB partitioning proteins, which function in plasmid and chromosome segregation between daughter cells before cell division [67]. We thus assume that this contig corresponds to a circular plasmid of Vallotia. Vallotia has three rRNA operons, similarly to its close relative, M. rhizoxinica [68]. In total, the Vallotia genome encoded 780 proteins (29 on the putative plasmid), 41 tRNAs, and 52 predicted pseudogenes (5 on the putative plasmid).The host-restricted lifestyle has a profound influence on bacterial genomes. Relaxed purifying selection on many redundant functions and increased genetic drift can lead to the accumulation of slightly deleterious mutations and the proliferation of mobile genetic elements [69,70,71,72]. Disruption of DNA repair genes can increase mutation rates, which promote gene inactivation [73]. Non-functional genomic regions get subsequently lost, and ancient obligate endosymbionts typically have tiny (≪0.8 Mb), gene-dense genomes with AT-biased nucleotide composition [2, 74, 75]. Facultative symbionts also possess accelerated rates of sequence evolution but have larger genomes ( >2 Mb) with variable coding densities following the age of their host-restricted lifestyle [76]. The number of pseudogenes in Vallotia and Profftia is higher than in ancient intracellular symbionts, which suggests an intermediate state of genomic reduction [2]. The only moderately reduced size and AT bias together with the low protein-coding density of the Vallotia and Profftia genomes was most similar to those of evolutionary young co-obligate partners of insects [76], for instance, “Ca. Pseudomonas adelgestsugas” in A. tsugae [23], Serratia symbiotica in Cinara cedri [77, 78], and the Sodalis-like symbiont of Philaenus spumarius, the meadow spittlebug [79].The evolutionary link between Vallotia and fungus-associated endosymbiontsHigh level of genomic synteny between Vallotia and M. rhizoxinica
Intracellular symbionts usually show a low level of genomic similarity to related bacteria. Rare examples of newly emerged bacteriocyte-associated symbionts of herbivorous insects pinpoint their source from plant-associated bacteria [4], gut bacteria [5], and other free-living bacteria [6].Genome alignments showed a low level of collinearity between the genomes of Profftia and its closest relatives. Among the relatives of Vallotia, a closed genome is available for M. rhizoxinica [68]. We therefore mostly focused on this fungus-associated symbiont as a reference for comparison with Vallotia.The Vallotia chromosome showed a surprisingly high level of synteny with the chromosome of M. rhizoxinica (Fig. 2A). However, its size was only ~40% of the fungus-associated symbiont chromosome. The putative plasmid of Vallotia was perfectly syntenic with the larger of the two plasmids of M. rhizoxinica (pBRH01), although the Vallotia plasmid was >90% smaller in size (72,431 bp versus 822,304 bp) [68]. Thus, the Vallotia plasmid showed a much higher level of reduction than the chromosome, which together with its lower G + C content and gene density suggests differential evolutionary constraints on these replicons.Fig. 2: High level of collinearity between the genomes of Vallotia and M. rhizoxinica.A Circos plot showing the synteny between the chromosome and plasmid of Vallotia and M. rhizoxinica, an endosymbiont of Rhizopus fungi. The outermost and the middle rings show genes in forward and reverse strand orientation, respectively. These include rRNA genes in red and tRNA genes in dark orange. The innermost ring indicates single-copy genes shared by M. rhizoxinica and Vallotia in black. Purple and dark yellow lines connect forward and reverse matches between the genomes, respectively. B Close up of the largest deletion on the chromosome of M. rhizoxinica and the syntenic region on the Vallotia chromosome. Genes are colored according to COG categories. Yellow: secondary metabolite biosynthesis; red: transposase; gray: unknown function; khaki: replication, recombination and repair; pink: lipid transport and metabolism; brown: protein turnover and chaperones; dark green: amino acid transport and metabolism; light green: cell envelope biogenesis; black: transcription. The figure was generated by Easyfig.Full size imageThe conservation of genome structure contrasts with the elevated number of transposases and inactive derivatives making up ~6% of the fungus-associated symbiont genome [68]. Transition to a host-restricted lifestyle is usually followed by a sharp proliferation of mobile genetic elements coupled with many genomic rearrangements [80,81,82]. However, mobile genetic elements get subsequently purged out of the genomes of strictly vertically transmitted symbionts via a mutational bias toward deletion and because of lack of opportunity for horizontal acquisition of novel genetic elements [71, 74]. Independent origins of the fungus and adelgid symbioses from free-living precursors would have likely resulted in extensive genome rearrangements due to the accumulation of mobile genetic elements, as seen, for instance, between different S. symbiotica strains in aphids [81]. In contrast to the fungus-associated symbiont, mobile elements are notably absent from the Vallotia genome, suggesting that they might have been lost early after the establishment of the adelgid symbiosis conserving high collinearity between the fungus- and adelgid-associated symbiont genomes. M. rhizoxinica is transmitted also horizontally among fungi and might have more exposure to foreign DNA, therefore at least part of the mobile elements could possibly be inserted into its genome after the host switch of the Vallotia precursor [61, 62].The observed high level of genome synteny between Vallotia and M. rhizoxinica genomes is consistent with the phylogenetic position of Vallotia interleaved within the clade of Rhizopus endosymbionts. This points toward a direct evolutionary link between these symbioses and a symbiont transition between the fungus and insect hosts.Shrinkage of the insect symbiont genomeDeletion of large genomic fragments—spanning many functionally unrelated genes—represents an important driving force of genome erosion especially at early stages of symbioses when selection on many functions is weak [3, 83]. Besides, gene loss also occurs individually and is ongoing, albeit at a much lower rate, even in ancient symbionts [75, 84, 85]. Both small and large deletions could be seen when comparing the Vallotia and M. rhizoxinica genomes. Several small deletions as small as one gene were observed sparsely in the entire length of the Vallotia genome within otherwise collinear regions. The largest genomic region missing from Vallotia encompassed 165 kbp on the M. rhizoxinica chromosome (Fig. 2B). The corresponding intergenic spacer was only 3843-bp long on the Vallotia genome between a phage shock protein and the Mfd transcription-repair-coupling factor, present both in Vallotia and M. rhizoxinica. Interestingly, this large genomic fragment included the large rhizoxin biosynthesis gene cluster (rhiIGBCDHEF), which is responsible for the production of rhizoxin, a potent antimitotic macrolide serving as a virulence factor for R. microsporus, the host of M. rhizoxinica [86]. A homologous gene cluster was also found in Pseudomonas fluorescens, and it has been suggested that it has been horizontally acquired by M. rhizoxinica [68, 86]. The rhi cluster is also present in M. endofungorum, therefore it was most likely already present in the genome of the common ancestor of the fungus- and adelgid-associated symbionts and got subsequently lost in Vallotia. Rhizoxin blocks microtubule formation in various types of eukaryotic cells [86, 87], thus the loss of this gene cluster in ancestral Vallotia could have contributed to the establishment of the adelgid symbiosis. However, this large deleted genomic region also contained several transposases and many other genes, such as argE and ilvA, coding for the final enzymes for ornithine and 2-oxobutanoate productions, which were located adjacent to each other at the beginning of this fragment. The largest deletion between the plasmids encompassed nearly 137 kbp of the megaplasmid of M. rhizoxinica and involved several non-ribosomal peptide synthetases (NRPS), insecticidal toxin complex (Tc) proteins, and a high number of transposases among others. M. rhizoxinica harbors 15 NRPS gene clusters [68] in total, all of which are absent in Vallotia. NRPSs are large multienzyme machineries that assemble various peptides, which might function as antibiotics, signal molecules, or virulence factors [88]. Insecticidal toxin complexes are bacterial protein toxins, which exhibit powerful insecticidal activity [89]. Two of such proteins are also present in the large deleted chromosomal region in close proximity to the rhizoxin biosynthesis gene cluster (Fig. 2B); however, their role in M. rhizoxinica remains elusive.The Vallotia genome encodes a subset of functions of the fungus-associated endosymbiontsThe number of protein-coding genes of Vallotia is less than one-third of those of M. rhizoxinica and M. endofungorum, although metabolic functions are already reduced in the fungus-associated endosymbionts compared to free-living Burkholderia species [68] (Figs. S4 and S5). When compared to the two genomes of the fungus-associated endosymbionts, only 53 proteins were specific to Vallotia (Fig. S6). All of these were short (on average 68 amino acid long) hypothetical proteins and most of them showed no significant similarity to other proteins in public databases. Whether these Vallotia-specific hypothetical proteins might be over-annotated/non-functional open reading frames or orphan genes with a yet unknown function [90, 91] needs further investigation. Four genes were present in Vallotia and M. rhizoxinica but were missing in M. endofungorum. These encoded for BioA and BioD in biotin biosynthesis, NagZ in cell wall recycling, and an MFS transporter. Fifteen genes, including, for instance, the MreB rod-shape-determining protein, glycosyltransferase and hit family proteins, genes in lipopolysaccharide, lipoate synthesis, and the oxidative pentose phosphate pathway, were shared between Vallotia and M. endofungorum only. The rest of the Vallotia genes, coding for 91% of all of its proteins, were shared among the fungus- and insect-associated endosymbionts.Comparing the genes present in both endosymbionts to those shared only by the fungus-associated endosymbionts (Fig. S7), we can infer selective functions maintained or lost during transition to insect endosymbiosis. Translation-related functions have been retained in the greatest measure in the group shared by all endosymbionts. Functions, where higher proportion of genes were specific to the fungus endosymbioses, were related to transcription, inorganic ion transport and metabolism, secondary metabolite biosynthesis, signal transduction, intracellular trafficking, secretion, vesicular transport, and defense mechanisms. Most of the proteins specific to either of the fungus-associated symbionts were homologous to transposases and integrases, transcriptional regulators, or had an unknown function.Fungus-associated endosymbionts encode a high number of transcriptional regulators (~5% of all genes in M. rhizoxinica) [68], but Vallotia has retained only a handful of such genes, which is a feature similar to other insect symbionts and might facilitate the overproduction of essential amino acids [75, 92].M. rhizoxinica is resistant against various β-lactams and has an arsenal of efflux pumps that might provide defense against antibacterial fungal molecules, the latter might also excrete virulence factors to the fungus cytosol (type I secretion) [68]. Besides, M. rhizoxinica encodes several genes for pilus formation; adhesion proteins; and type II, type III, and type IV secretion systems, which likely play a central role in host infection and manipulation in the bacteria–fungus symbiosis [68, 93, 94]. However, all of the corresponding genes are missing in Vallotia. Thus, neither of these mechanisms likely play a role in the adelgid symbiosis. Indeed, we could not even detect remnants of these genes in the Vallotia genome, except for a type II secretion system protein as a pseudogene. Loss of these functions is consistent with a strictly vertical transmission of Vallotia between host generations. Transovarial transmission likely does not require active infection mechanisms, and the endosymbionts rather move between the insect cells in a passive manner via an endocytic/exocytic vesicular route [12, 95]. In contrast, M. rhizoxinca is also able to spread horizontally among fungi and re-infect cured Rhizopus strains under laboratory conditions [61, 62].Differential reduction of metabolic pathways in Vallotia and Profftia
Although compared to their closest free-living relatives both Vallotia and Profftia have lost many genes in all functional categories, both retained the highest number of genes in translation-related functions (Fig. S4). Besides, functions related to cell division, nucleotide and coenzyme transport and metabolism, DNA replication and repair, posttranslational modification, and cell envelope biogenesis are reduced to a lesser extent in both endosymbionts. As a consequence, most of the genes of Vallotia and Profftia are devoted to translation and cell envelope biogenesis, which make up higher proportions of their genomes than in related bacteria (Fig. S5). Retention of a minimal set of genes involved in central cellular functions such as translation, transcription, and replication is a typical feature of reduced genomes, even extremely tiny ones of long-term symbionts [75]. However, ancient intracellular symbionts usually miss a substantial number of genes for the production of the cell envelope and might rely on host-derived membrane compounds [96,97,98].Based on pathway reconstructions, both Vallotia (Fig. S8) and Profftia (Fig. S9) have a complete gene set for peptidoglycan, fatty acid, and phospholipid biosynthesis and retained most of the genes for the production of lipid A, LPS core, and the Lpt LPS transport machinery. Besides, we found a partial set of genes for O antigen biosynthesis in the Vallotia genome. Regarding the membrane protein transport and assembly, both adelgid endosymbionts have the necessary genes for Sec and signal recognition particle translocation and the BAM outer membrane protein assembly complex. Profftia also has a complete Lol lipoprotein trafficking machinery (lolABCDE), which can deliver newly matured lipoproteins from the inner membrane to the outer membrane [99]. In addition, Profftia has a near-complete gene set for the Tol-Pal system; however, tolA has been pseudogenized suggesting an ongoing reduction of this complex. Further, both adelgid endosymbionts have retained mrdAB and mreBCD having a role in the maintenance of cell wall integrity and morphology [100, 101]. The observed well-preserved cellular functions for cell envelope biogenesis and integrity are consistent with the rod-shaped cell morphology of Profftia and Vallotia [14], contrasting the spherical/pleomorphic cell shape of ancient endosymbionts, such as Annandia in A. tsugae and Pineus species [10, 11, 15].Regarding the central metabolism, Vallotia lacks 6-phosphofructokinase but has a complete gene set for gluconeogenesis and the tricarboxylic acid (TCA) cycle. TCA cycle genes are typically lost in long-term symbionts but are present in facultative and evolutionarily recent obligate endosymbionts [79, 82, 102]. Interestingly, Vallotia does not have a recognized sugar transporter. Similarly to M. rhizoxinica [68], a glycerol kinase gene next to a putative glycerol uptake facilitator protein is present on its plasmid. However, the latter gene has a frameshift mutation and a premature stop codon in the first 40% of the sequence and whether it can still produce a functional protein remains unknown.Profftia can convert acetyl-CoA to acetate for energy but lacks TCA cycle genes, a feature characteristic to more reduced genomes, such as, for instance, Annandia in A. tsugae [23]. Profftia has import systems for a variety of organic compounds, such as murein tripeptides, phospholipids, thiamine, spermidine and putrescine, 3-phenylpropionate, and a complete phosphotransferase system for the uptake of sugars.NADH dehydrogenase, ATP synthase, and cytochrome oxidases (bo/bd-1) are encoded on both adelgid symbiont genomes. However, Vallotia is not able to produce ubiquinone and six pseudogenes in its genome indicate a recent inactivation of this pathway (Fig. S10).Profftia retained more functions in inorganic ion transport and metabolism, while Vallotia had a characteristically higher number of genes related to amino acid biosynthesis (see its function below) and nucleotide transport and metabolism (Fig. S4). For instance, Profftia can take up sulfate and use it for assimilatory sulfate reduction and cysteine production, and it has also retained many genes for heme biosynthesis (Fig. S9). However, it cannot produce inosine-5-phosphate and uridine 5’-monophosphate precursors for the de novo synthesis of purine and pyrimidine nucleotides and thus would need to import these compounds.Notably, although core genes in DNA replication and repair [70] are well preserved, multiple pseudogenes may indicate an ongoing erosion of DNA repair functions in the genomes. These include genes for the UvrABC nucleotide excision repair complex in both adelgid symbionts, helicases (recG, recQ), mismatch repair genes (mutL, mutS; the MutHLS complex is also missing in Profftia), and alkA encoding a DNA glycosylase in Vallotia.Taken together, their moderately reduced, gene-sparse genomes but still versatile metabolic capabilities support that Vallotia and Profftia are evolutionarily recently acquired endosymbionts. This is following their occurrence in lineages of adelgids, which likely diversified relatively recently, ~60 and ~47 million years ago, respectively, from the remaining clades of Adelgidae [8].
Vallotia and Profftia are both obligatory nutritional symbiontsComplementary functions in essential amino acid provisionVallotia and Profftia complement each other’s role in the essential amino acid synthesis, thus have a co-obligatory status in the A. laricis/A. tardus symbiosis (Fig. 3). Although Vallotia likely generates most essential amino acids, solely Profftia can produce chorismate, a key precursor for the synthesis of phenylalanine and tryptophan. Profftia is likely responsible for the complete biosynthesis of phenylalanine as it has a full set of genes for this pathway. It can also convert chorismate to anthranilate; however, further genes for tryptophan biosynthesis are only present in the Vallotia genome. Thus, Vallotia likely takes up anthranilate for tryptophan biosynthesis. Anthranilate synthase (trpEG), is subject to negative feedback regulation by tryptophan [103], thus partition of this rate-limiting step between the co-symbionts can enhance overproduction of the amino acid and might stabilize dual symbiotic partnerships at an early stage of coexistence. The production of tryptophan is partitioned between Vallotia and Profftia similarly as seen in other insect symbioses [77, 78, 104], and it is also shared but is more redundant between the Annandia and Pseudomonas symbionts of A. tsugae [23]. The Vallotia–Profftia system generally shows a lower level of functional overlap between the symbionts and is more unbalanced than the Annandia–Pseudomonas association. In the latter, redundant genes are present also in the synthesis of phenylalanine, threonine, lysine, and arginine, and Annandia can produce seven and the Pseudomonas partner five essential amino acids with the contribution of host genes [23].Fig. 3: Division of labor in amino acid biosynthesis and transport between Vallotia and Profftia showing co-obligatory status of endosymbionts of A. laricis/tardus.Amino acids produced by Vallotia and Profftia are shown in blue and red, respectively. Bolded texts indicate essential amino acids. The insect host likely supplies ornithine, homocysteine, 2-oxobutanoate, and glutamine. Other compounds that cannot be synthesized by the symbionts are shown in gray italics.Full size imageThe Vallotia genome encodes for all the enzymes for the synthesis of five essential amino acids (histidine, leucine, valine, lysine, threonine). ArgG and tyrB among the essential amino acid synthesis-related genes are only present on the plasmid of Vallotia, which might be a reason that the plasmid is still part of its genome. However, neither of the endosymbionts can produce ornithine, 2-oxobutanoate, and homocysteine de novo, which are key for the biosynthesis of arginine, isoleucine, and methionine, respectively. The corresponding functions are also missing from the Annandia–Pseudomonas system [23]. These compounds are thus likely supplied by the insect host, as seen for instance in aphids, mealybugs, and psyllids, where the respective genes are present in the insect genomes and are typically overexpressed within the bacteriome [97, 105, 106]. The metC and argA genes are still present as pseudogenes in Vallotia suggesting a recent loss of these functions in methionine and arginine biosynthesis, respectively.In most plant sap-feeding insects harboring a dual symbiotic system, typically the more ancient symbiont provides most of the essential amino acids [77, 107]. Given its prominent role in nutrient provision and its presence in both larch- and Douglas fir-associated adelgids, Vallotia might be the older symbiont. Loss of functions in chorismate and anthranilate biosynthesis might have led to the fixation of Profftia in the system.Vallotia and Profftia have more redundant functions in non-essential amino acid production (Fig. 3). Only Profftia can produce cysteine and tyrosine, while none of the symbionts can build up glutamine, thus this latter amino acid is likely supplied by the insect bacteriocytes.The presence of relevant transporters can complement missing functions in amino acid synthesis (Fig. 3). For instance, Profftia has a high-affinity glutamine ABC transporter and three symporters (BrnQ, Mtr, TdcC), which can import five among the essential amino acids that can be produced by Vallotia. Vallotia might excrete isoleucine, valine, and leucine via AzICD, a putative branched-chain amino acid efflux pump [108], and these amino acids could be taken up by Profftia via BrnQ and would be readily available also for the insect host.B vitamin provision by Vallotia
Regarding the B vitamin synthesis, Vallotia is likely able to produce thiamine (B1), riboflavin (B2), pantothenate (B5), pyridoxine (B6), biotin (B7), and folic acid (B9) (Fig. S11). Although Vallotia misses some genes of the canonical pathways, alternative enzymes and host-derived compounds might bypass these reactions, as detailed in the Supplementary Material. Profftia has only a few genes related to B vitamin biosynthesis. Three pseudogenes (ribAEC) in the riboflavin synthesis pathway indicate that these functions might have been lost recently in this symbiont (Fig. S11). More

1.Lomolino, M. V. Elevation gradients of species-density: historical and prospective views. Glob. Ecol. Biogeogr. 10, 3–13 (2001).Article 

Google Scholar 
2.McCain, C. M. Global analysis of reptile elevational diversity. Glob. Ecol. Biogeogr. 19, 541–553 (2010).
Google Scholar 
3.Quintero, I. & Jetz, W. Global elevational diversity and diversification of birds. Nature 555, 246–250 (2018).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
4.Orme, C. D. L. et al. Global hotspots of species richness are not congruent with endemism or threat. Nature 436, 1016–1019 (2005).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
5.Rahbek, C. et al. Humboldt’s enigma: what causes global patterns of mountain biodiversity? Science 365, 1108–1113 (2019).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
6.Wiens, J. J., Parra-Olea, G., García-París, M. & Wake, D. B. Phylogenetic history underlies elevational biodiversity patterns in tropical salamanders. Proc. R. Soc. B 274, 919–928 (2007).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
7.Pigot, A. L., Trisos, C. H. & Tobias, J. A. Functional traits reveal the expansion and packing of ecological niche space underlying an elevational diversity gradient in passerine birds. Proc. R. Soc. B 283, 20152013 (2016).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
8.Körner, C. & Spehn, E. M. (eds) Mountain Biodiversity: A Global Assessment (CRC Press, 2002).9.Merckx, V. S. F. T. et al. Evolution of endemism on a young tropical mountain. Nature 524, 347–350 (2015).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
10.Fjeldsa, J. Geographical patterns for relict and young species of birds in Africa and South America and implications for conservation priorities. Biodivers. Conserv. 3, 207–226 (1994).Article 

Google Scholar 
11.Jetz, W., Rahbek, C. & Colwell, R. K. The coincidence of rarity and richness and the potential signature of history in centres of endemism. Ecol. Lett. 7, 1180–1191 (2004).Article 

Google Scholar 
12.Weir, J. T. Divergent timing and patterns of species accumulation in lowland and highland Neotropical birds. Evolution 60, 842–855 (2006).PubMed 
Article 
PubMed Central 

Google Scholar 
13.Hughes, C. & Eastwood, R. Island radiation on a continental scale: exceptional rates of plant diversification after uplift of the Andes. Proc. Natl Acad. Sci. USA 103, 10334–10339 (2006).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
14.Cozzarolo, C.-S. et al. Biogeography and ecological diversification of a mayfly clade in New Guinea.Front. Ecol. Evol. 7, 233 (2019).Article 

Google Scholar 
15.Davies, T. J., Savolainen, V., Chase, M. W., Moat, J. & Barracloug, T. G. Environmental energy and evolutionary rates in flowering plants. Proc. R. Soc. B 271, 2195–2200 (2004).PubMed 
PubMed Central 
Article 

Google Scholar 
16.Graves, G. R. Linearity of geographic range and its possible effect on the population structure of andean birds. Auk 105, 47–52 (1988).Article 

Google Scholar 
17.Janzen, D. H. Why mountain passes are higher in the tropics. Am. Nat. 101, 233–249 (1967).Article 

Google Scholar 
18.Cai, T. et al. What makes the Sino-Himalayan mountains the major diversity hotspots for pheasants? J. Biogeogr. 45, 640–651 (2018).Article 

Google Scholar 
19.Rana, S. K., Gross, K. & Price, T. D. Drivers of elevational richness peaks, evaluated for trees in the east Himalaya. Ecology 100, e02548 (2019).PubMed 
Article 
PubMed Central 

Google Scholar 
20.Rahbek, C. et al. Building mountain biodiversity: geological and evolutionary processes. Science 365, 1114–1119 (2019).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
21.Ribas, C. C., Moyle, R. G., Miyaki, C. Y. & Cracraft, J. The assembly of montane biotas: linking Andean tectonics and climatic oscillations to independent regimes of diversification in Pionus parrots. Proc. R. Soc. B 274, 2399–2408 (2007).PubMed 
PubMed Central 
Article 

Google Scholar 
22.Schwery, O. et al. As old as the mountains: the radiations of the Ericaceae. N. Phytologist 207, 355–367 (2015).Article 

Google Scholar 
23.Bates, J. M. & Zink, R. M. Evolution into the Andes: molecular evidence for species relationships in the genus Leptopogon. Auk 111, 507–515 (1994).
Google Scholar 
24.Roy, M. S. Recent diversification in African greenbuls (Pycnonotidae: Andropadus) supports a montane speciation model. Proc. R. Soc. B 264, 1337–1344 (1997).PubMed Central 
Article 

Google Scholar 
25.Garcia-Moreno, J. et al. Pre-Pleistocene differentiation among chat-tyrants. Condor 100, 629–640 (1998).Article 

Google Scholar 
26.Oliveros, C. H. et al. Earth history and the passerine superradiation. Proc. Natl Acad. Sci. USA 116, 7916–7925 (2019).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
27.Jetz, W., Thomas, G. H., Joy, J. B., Hartmann, K. & Mooers, A. O. The global diversity of birds in space and time. Nature 491, 444–448 (2012).CAS 
Article 

Google Scholar 
28.Title, P. O. & Rabosky, D. L. Tip rates, phylogenies and diversification: what are we estimating, and how good are the estimates? Methods Ecol. Evol. 10, 821–834 (2019).Article 

Google Scholar 
29.Herrera-Alsina, L., van Els, P. & Etienne, R. S. Detecting the dependence of diversification on multiple traits from phylogenetic trees and trait data. Syst. Biol. 68, 317–328 (2019).PubMed 
Article 
PubMed Central 

Google Scholar 
30.Weir, J. T. & Schluter, D. The latitudinal gradient in recent speciation and extinction rates of birds and mammals. Science 315, 1574–1576 (2007).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
31.Derryberry, E. P. et al. Lineage diversification and morphological evolution in a large-scale continental radiation: the Neotropical ovenbirds and woodcreepers (Aves: Furnariidae). Evolution 65, 2973–2986 (2011).PubMed 
PubMed Central 
Article 

Google Scholar 
32.Fjeldså, J., Bowie, R. C. K. & Rahbek, C. The role of mountain ranges in the diversification of birds. Annu. Rev. Ecol. Evol. Syst. 43, 249–265 (2012).Article 

Google Scholar 
33.Chazot, N. et al. Into the Andes: multiple independent colonizations drive montane diversity in the Neotropical clearwing butterflies Godyridina. Mol. Ecol. 25, 5765–5784 (2016).PubMed 
Article 
PubMed Central 

Google Scholar 
34.Elias, M. et al. Out of the Andes: oatterns of diversification in clearwing butterflies. Mol. Ecol. 18, 1716–1729 (2009).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
35.McGuire, J. A., Witt, C. C., Altshuler, D. L. & Remsen, J. V. Phylogenetic systematics and biogeography of hummingbirds: Bayesian and maximum likelihood analyses of partitioned data and selection of an appropriate partitioning strategy. Syst. Biol. 56, 837–856 (2007).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
36.Brumfield, R. T. & Edwards, S. V. Evolution into and out of the Andes: a Bayesian analysis of historical diversification in Thamnophilus antshrikes. Evolution 61, 346–367 (2007).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
37.Zhou, C. et al. Genome-wide analysis sheds light on the high-altitude adaptation of the buff-throated partridge (Tetraophasis szechenyii). Mol. Genet. Genom. 295, 31–46 (2020).CAS 
Article 

Google Scholar 
38.Xu, Z., He, J. & Wang, J. Hypoxia affects the resistance of Scylla paramamosain to Vibrio alginolyticus via changes of energy metabolism. Aquac. Rep. 19, 100565 (2021).Article 

Google Scholar 
39.Storz, J. F., Scott, G. R. & Cheviron, Z. A. Phenotypic plasticity and genetic adaptation to high-altitude hypoxia in vertebrates. J. Exp. Biol. 213, 4125–4136 (2010).PubMed 
PubMed Central 
Article 

Google Scholar 
40.Scott, G. R. Elevated performance: the unique physiology of birds that fly at high altitudes. J. Exp. Biol. 214, 2455–2462 (2011).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
41.Projecto-Garcia, J. et al. Repeated elevational transitions in hemoglobin function during the evolution of Andean hummingbirds. Proc. Natl Acad. Sci. USA 110, 20669–20674 (2013).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
42.Scott, G. R. et al. Molecular evolution of cytochrome C oxidase underlies high-altitude adaptation in the bar-headed goose. Mol. Biol. Evol. 28, 351–363 (2011).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
43.Schumm, M., White, A. E., Supriya, K. & Price, T. D. Ecological limits as the driver of bird species richness patterns along the east Himalayan elevational gradient. Am. Nat. 195, 802–817 (2020).PubMed 
Article 
PubMed Central 

Google Scholar 
44.Malpica, A., Covarrubias, S., Villegas-Patraca, R. & Herrera-Alsina, L. Ecomorphological structure of avian communities changes upon arrival of wintering species. Basic Appl. Ecol. 24, 60–67 (2017).Article 

Google Scholar 
45.Etienne, R. S. et al. A minimal model for the latitudinal diversity gradient suggests a dominant role for ecological limits. Am. Nat. 194, E122–E133 (2019).PubMed 
Article 
PubMed Central 

Google Scholar 
46.Freeman, B. G., Scholer, M. N., Ruiz-Gutierrez, V. & Fitzpatrick, J. W. Climate change causes upslope shifts and mountaintop extirpations in a tropical bird community. Proc. Natl Acad. Sci. USA 115, 11982–11987 (2018).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
47.Bouckaert, R. et al. BEAST 2: a software platform for Bayesian evolutionary analysis. PLoS Comput. Biol. 10, e1003537 (2014).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
48.Braun, E. L., Cracraft, J. & Houde, P. in Avian Genomics in Ecology and Evolution (ed. Kraus, R. H. S.) 151–210 (Springer, 2019).49.del Hoyo, J., Elliott, A., Sargatal, J., Christie, D. A. & Kirwan, G. Handbook of the Birds of the World (Lynx Edicions, 2016).50.Chapman, F. M. et al. The distribution of bird life in Ecuador: a contribution to a study of the origin of Andean bird-life. Bull. Am. Mus. Nat. Hist. 55, 1–784 (1926).
Google Scholar 
51.Maddison, W. P., Midford, P. E. & Otto, S. P. Estimating a binary character’s effect on speciation and extinction. Syst. Biol. 56, 701–710 (2007).PubMed 
Article 
PubMed Central 

Google Scholar 
52.Beaulieu, J. M. & O’Meara, B. C. Detecting hidden diversification shifts in models of trait-dependent speciation and extinction. Syst. Biol. 65, 583–601 (2016).PubMed 
Article 
PubMed Central 

Google Scholar 
53.Harmon, L. J., Weir, J. T., Brock, C. D., Glor, R. E. & Challenger, W. GEIGER: investigating evolutionary radiations. Bioinformatics 24, 129–131 (2008).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
54.Daru, B., Karunarathne, P. & Schliep, K. phyloregion: R package for biogeographic regionalization and spatial conservation. Methods Ecol. Evol. 11, 1483–1491 (2020).Article 

Google Scholar  More

1.Hobbs, R. J. et al. Restoration ecology: the challenge of social values and expectations. Front. Ecol. Environ. 2, 43–38 (2004).Article 

Google Scholar 
2.Harris, J. A., Hobbs, R. J., Higgs, E. & Aronson, J. C. Ecological restoration and global climate change. Restor. Ecol. 14, 170–176 (2006).3.Aronson, J. C. & Vallejo, R. in Restoration Ecology: The New Frontier (eds. van Andel, J. & Aronson, J. C.) (John Wiley & Sons, 2009).4.Suding, K. et al. Committing to ecological restoration. Science 348, 638–640 (2015).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
5.Plaza, C. et al. Soil resources and element stocks in drylands to face global issues. Sci. Rep. 8, 13788 (2018).6.Aronson, J., Goodwin, N., Orlando, L., Eisenberg, C. & Cross, A. T. A world of possibilities: six restoration strategies to support the United Nation’s Decade on Ecosystem Restoration. Restor. Ecol. 28, 730–736 (2020).Article 

Google Scholar 
7.Drylands and Land Degradation (IUCN, 2017).8.Bainbridge, D. A. A Guide for Desert and Dryland Restoration: New Hope for Arid Lands (Island Press, 2012).9.Millennium Ecosystem Assessment Findings (Millennium Ecosystem Assessment, 2005).10.Reynolds, J. F., Maestre, F. T., Kemp, P. R., Stafford-Smith, D. M. & Lambin, E. in Terrestrial Ecosystems in a Changing World (eds. Canadell, J. G., Pataki, D. E. & Pitelka, L. F.) 247–257 (Springer, 2007); https://doi.org/10.1007/978-3-540-32730-1_2011.Hoover, D. L. et al. Traversing the wasteland: a framework for assessing ecological threats to drylands. BioScience 70, 35–47 (2020).Article 

Google Scholar 
12.Hardegree, S. P., Jones, T. A., Roundy, B. A., Shaw, N. L. & Monaco, T. A. in Conservation Benefits of Rangeland Practices 171–213 (United States Department of Agriculture, 2011).13.James, J. J., Svejcar, T. J. & Rinella, M. J. Demographic processes limiting seedling recruitment in arid grassland restoration. J. Appl. Ecol. 48, 961–969 (2011).Article 

Google Scholar 
14.Okin, G. S. et al. Connectivity in dryland landscapes: shifting concepts of spatial interactions. Front. Ecol. Environ. 13, 20–27 (2015).Article 

Google Scholar 
15.Svejcar, L. N. & Kildisheva, O. A. The age of restoration: challenges presented by dryland systems. Plant Ecol. 218, 1–6 (2017).Article 

Google Scholar 
16.Safriel, U. et al. Dryland Systems. Ecosystems and Human Well-being: Current State and Trends.: Findings of the Condition and Trends Working Group 623–662 (Millennium Ecosystem Assessment, 2005).17.Ward, D. The Biology of Deserts (Oxford Univ. Press, 2016).18.Li, Y., Chen, Y. & Li, Z. Dry/wet pattern changes in global dryland areas over the past six decades. Glob. Planet. Change 178, 184–192 (2019).Article 

Google Scholar 
19.Prăvălie, R., Bandoc, G., Patriche, C. & Sternberg, T. Recent changes in global drylands: evidences from two major aridity databases. Catena 178, 209–231 (2019).Article 

Google Scholar 
20.Yao, J. et al. Accelerated dryland expansion regulates future variability in dryland gross primary production. Nat. Commun. 11, 1665 (2020).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
21.Aridity Zones and Dryland Populations: An Assessment of Population Levels in the World’s Drylands with Reference to Africa (UNSO/UNDP, 1997); http://digitallibrary.un.org/record/43231222.van den Berg, L. & Kellner, K. Restoring degraded patches in a semi-arid rangeland of South Africa. J. Arid. Environ. 61, 497–511 (2005).Article 

Google Scholar 
23.Valkó, O. et al. Cultural heritage and biodiversity conservation – plant introduction and practical restoration on ancient burial mounds. Nat. Conserv. 24, 65–80 (2018).Article 

Google Scholar 
24.Louhaichi, M., Clifton, K. & Hassan, S. Direct seeding of Salsola vermiculata for rehabilitation of degraded arid and semi-arid rangelands. Range Manag. Agrofor. 35, 182–187 (2014).
Google Scholar 
25.Pérez, D. R., González, F., Ceballos, C., Oneto, M. E. & Aronson, J. Direct seeding and outplantings in drylands of Argentinean Patagonia: estimated costs, and prospects for large-scale restoration and rehabilitation. Restor. Ecol. 27, 1105–1116 (2019).Article 

Google Scholar 
26.Kiehl, K., Kirmer, A., Donath, T. W., Rasran, L. & Hölzel, N. Species introduction in restoration projects: evaluation of different techniques for the establishment of semi-natural grasslands in Central and Northwestern Europe. Basic Appl. Ecol. 11, 285–299 (2010).Article 

Google Scholar 
27.Miguel, M. F., Butterfield, H. S. & Lortie, C. J. A meta-analysis contrasting active versus passive restoration practices in dryland agricultural ecosystems. PeerJ 8, e10428 (2020).PubMed 
PubMed Central 
Article 

Google Scholar 
28.Kildisheva, O. A., Erickson, T. E., Merritt, D. J. & Dixon, K. W. Setting the scene for dryland recovery: an overview and key findings from a workshop targeting seed-based restoration. Restor. Ecol. 24, S36–S42 (2016).Article 

Google Scholar 
29.Lewandrowski, W., Erickson, T. E., Dixon, K. W. & Stevens, J. C. Increasing the germination envelope under water stress improves seedling emergence in two dominant grass species across different pulse rainfall events. J. Appl. Ecol. 54, 997–1007 (2017).CAS 
Article 

Google Scholar 
30.Ladouceur, E. & Shackelford, N. The power of data synthesis to shape the future of the restoration community and capacity. Restor. Ecol. 29, e13251 (2020).
Google Scholar 
31.Temperton, V. M., Baasch, A., von Gillhaussen, P. & Kirmer, A. in Foundations of Restoration Ecology (eds. Palmer, M. A., Zedler, J. B. & Falk, D. A.) 245–270 (Island Press/Center for Resource Economics, 2016); https://doi.org/10.5822/978-1-61091-698-1_932.Hulvey, K. B. & Aigner, P. A. Using filter-based community assembly models to improve restoration outcomes. J. Appl. Ecol. 51, 997–1005 (2014).Article 

Google Scholar 
33.van Wilgen, B. W. The evolution of fire and invasive alien plant management practices in fynbos. S. Afr. J. Sci. 105, 335–342 (2009).
Google Scholar 
34.Arianoutsoua, M. & Vilà, M. Fire and invasive plant species in the Mediterranean Basin. Isr. J. Ecol. Evol. 58, 195–203 (2012).
Google Scholar 
35.Leger, E. A. & Baughman, O. W. What seeds to plant in the Great Basin? Comparing traits prioritized in native plant cultivars and releases with those that promote survival in the field. Nat. Areas. J. 35, 54–68 (2015).Article 

Google Scholar 
36.Porensky, L. M., Vaughn, K. J. & Young, T. P. Can initial intraspecific spatial aggregation increase multi-year coexistence by creating temporal priority? Ecol. Appl. 22, 927–936 (2012).PubMed 
Article 
PubMed Central 

Google Scholar 
37.FAOSTAT Statistical Database (Food and Agriculture Organization of the United Nations, 1997).38.Balazs, K. R. et al. The right trait in the right place at the right time: matching traits to environment improves restoration outcomes. Ecol. Appl. 30, e02110 (2020).PubMed 
Article 
PubMed Central 

Google Scholar 
39.Knutson, K. C. et al. Long-term effects of seeding after wildfire on vegetation in Great Basin shrubland ecosystems. J. Appl. Ecol. 51, 1414–1424 (2014).Article 

Google Scholar 
40.Brown, C. S. & Bugg, R. L. Effects of established perennial grasses on introduction of native forbs in California. Restor. Ecol. 9, 38–48 (2001).Article 

Google Scholar 
41.Porensky, L. M. et al. Arid old-field restoration: native perennial grasses suppress weeds and erosion, but also suppress native shrubs. Agric. Ecosyst. Environ. 184, 135–144 (2014).Article 

Google Scholar 
42.Hardegree, S. P. et al. Hydrothermal assessment of temporal variability in seedbed microclimate. Rangel. Ecol. Manag. 66, 127–135 (2013).Article 

Google Scholar 
43.Copeland, S. M. et al. Long-term trends in restoration and associated land treatments in the southwestern United States. Restor. Ecol. 26, 311–322 (2018).Article 

Google Scholar 
44.Abella, S. R., Craig, D. J., Smith, S. D. & Newton, A. C. Identifying native vegetation for reducing exotic species during the restoration of desert ecosystems. Restor. Ecol. 20, 781–787 (2012).Article 

Google Scholar 
45.Mulroy, T. W. & Rundel, P. W. Annual plants: adaptations to desert environments. BioScience 27, 109–114 (1977).Article 

Google Scholar 
46.Leger, E. A., Goergen, E. M. & Forbis de Queiroz, T. Can native annual forbs reduce Bromus tectorum biomass and indirectly facilitate establishment of a native perennial grass? J. Arid. Environ. 102, 9–16 (2014).Article 

Google Scholar 
47.Gutiérrez, J. R., Arancio, G. & Jaksic, F. M. Variation in vegetation and seed bank in a Chilean semi-arid community affected by ENSO 1997. J. Veg. Sci. 11, 641–648 (2000).Article 

Google Scholar 
48.Venable, D. L. Bet hedging in a guild of desert annuals. Ecology 88, 1086–1090 (2007).PubMed 
Article 
PubMed Central 

Google Scholar 
49.Baskin, C. C. Seed ecology: a diverse and vibrant field of study. Seed Sci. Res. 27, 61–64 (2017).Article 

Google Scholar 
50.Padilla, F. M., Ortega, R., Sánchez, J. & Pugnaire, F. I. Rethinking species selection for restoration of arid shrublands. Basic Appl. Ecol. 10, 640–647 (2009).Article 

Google Scholar 
51.SER International Primer on Ecological Restoration (SER, 2004).52.The Plant List (WFO, 2013).53.Seed Information Database (Royal Botanic Gardens, Kew, 2019).54.Kattge, J. et al. TRY plant trait database – enhanced coverage and open access. Glob. Change Biol. 26, 119–188 (2020).Article 

Google Scholar 
55.USDA, NRCS. The PLANTS Database (National Plant Data Team, 2020).56.Western Australian Herbarium. FloraBase—the Western Australian Flora (Department of Biodiversity, Conservation and Attractions, 1998).57.Fick, S. E. & Hijmans, R. J. Worldclim 2: new 1-km spatial resolution climate surfaces for global land areas. Int. J. Climatol. 37, 4302–4315 (2017).58.Trabucco, A. & Zomer, R. J. Global Aridity Index and Potential Evapo-Transpiration (ET0) Climate Database, v3 (CGIAR Consortium for Spatial Information, 2019).59.Barrow, C. J. World atlas of desertification (United Nations Environment Programme). Land Degrad. Dev. 3, 249–249 (1992).Article 

Google Scholar 
60.Brooks, M. E. et al. glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. R J. 9, 378–400 (2017).Article 

Google Scholar 
61.R Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2017).62.Crawley, M. J. in The R Book 569–591 (Wiley, 2007).63.Wortley, L., Hero, J.-M. & Howes, M. Evaluating ecological restoration success: a review of the literature. Restor. Ecol. 21, 537–543 (2013).Article 

Google Scholar  More

Bioleaching processVariation of pH and ORP during bioleaching processpH and ORP of the sludge are widely known to be the important parameters influencing heavy metal solubilization during bioleaching process, as well as the activity of iron-oxidizing microorganisms10,26,27. The variation of sludge pH and ORP during the single bioleaching process is presented in Fig. 1.Figure 1Variation of pH and ORP during bioleaching process.Full size imageAn appropriate pH could enhance the activities of microbes, affecting the release of metals and the stability of metal ions in the liquid phase5. As shown in Fig. 1, the pH value of sewage sludge quickly decreased from 6.44 to 3.07 in the first 6 days, due to the oxidation of Fe2+ and metal sulfides, the production of sulfuric acid, ferric hydroxide and jarosite from the hydrolysis of Fe3+18. Then the pH gradually decreased to 2.89 on the 10th day. The change of ORP followed an opposite trend. ORP value of the sludge rapidly increased from − 155.6 mV to 480.0 mV in the first 6 days, then to 505.0 mV in the following 4 days, due to the oxidation of Fe2+ to Fe3+ by leaching microorganisms.Heavy metals solubilization and chemical speciation distribution during bioleaching processThe removal of heavy metals during bioleaching process and the distribution of chemical fractions of heavy metals before and after bioleaching are presented in Figs. 2 and 3, respectively. The single bioleaching led to the removal of Zn, Cu, Cd, Cr, Mn, Ni, As and Pb of 67.28%, 50.78%, 64.86%, 6.32%, 56.15%, 49.83%, 20.78% and 10.52% in 10 days, respectively. The solubilization efficiency was highly related to the evolution of pH and ORP, the chemical fraction distributions and the nature of heavy metals.Figure 2Removal of heavy metals during bioleaching process.Full size imageFigure 3Chemical speciation distributions of heavy metals in raw sludge and bioleached sludge, total concentration of heavy metals in the raw sludge was set as 100% (RS raw sludge, BS bioleached sludge).Full size imageFigure 2 illustrated that Zn had the highest solubilization and removal efficiency. It was found that below the threshold pH of 6–6.5, Zn could be dissolved28. Thus, the dissolving out of Zn had started at the beginning of leaching experiment with a removal percentage of 10.15% on the 2nd day. Yet the quick solubilization of Zn was observed from the 4th day (pH 4.01). And until the 6th day (pH 3.00) when the solubilization percentage of Zn was 65.71%, the leaching rate of Zn was slowed down due to the stable pH. In the raw sludge, Zn mainly existed in mobile forms (exchangeable/acid soluble and reducible forms) as shown in Fig. 3. After bioleaching, the solubilization efficiencies of Zn in exchangeable/acid soluble form and reducible form was 58.66% and 87.93%, respectively. Meanwhile, 48.27% of Zn in oxidizable form was also dissolved out due to the oxidation of metal sulfide and loss of sludge organic matter. However, Zn in residual form remained almost unchanged in the bioleached sludge due to its high stability.It has been pointed out that Cu could be rapidly solubilized below pH of 3.7 or under a high ORP condition29. As shown in Fig. 2, in the first 4 days, the solubilization efficiency of Cu was relatively low (11.44%). The removal rate of Cu increased rapidly to 43.54% on the 6th day due to the increase of ORP (480 mV). The proportion of Cu in exchangeable/acid soluble form increased by 55.16% after bioleaching, probably because the solubilized Cu2+ was re-adsorbed on the EPS of sludge cells30,31. Most of Cu was present in reducible and oxidizable forms in the raw sludge as shown in Fig. 3, because the complexation of copper and organic materials was relatively stable30,32,33. The removal percentages of Cu in reducible and oxidizable forms were 71.11% and 61.83% after bioleaching, respectively, which was the main reason for Cu removal.Cd could be solubilized rapidly under acidic conditions as shown in Fig. 2, which is consistent with the previous study34. The solubilization of Cd could be finished in 6 days with the removal rate of 64.36%. Cd was mainly present in mobile forms (91.07%) as shown in Fig. 3, which agreed with the findings of Zeng et al.35 Thus, the acid dissolution was the main removal mechanism of Cd34. Due to the low pH of the bioleached sludge, the content of Cd in mobile forms decreased by 62.77% after bioleaching. Furthermore, Cd in immobile forms (oxidizable and residual forms) also reduced significantly.The previous study found that Cr was relatively stable with the dissolved pH threshold of 2.3–3.028. Although the percentage of Cr present in mobile forms was over 40%, the removal rate of Cr (6.32%) was the lowest among all the heavy metals investigated as shown in Fig. 2, because the lowest pH of the bioleached sludge was about 2.9, which was close to the dissolution threshold limit of Cr.As shown in Fig. 2, Mn and Ni were solubilized quickly in the first 4 days. The solubilization percentage of Mn and Ni were 56.14% and 49.83% after bioleaching, respectively. Mn and Ni mainly existed in the mobile forms (Mn 82.05%, Ni 76.08%). In the early stage of bioleaching, the removal rates of Mn and Ni were closely related to the variation of pH and displayed obvious acid dissolution mechanism. After bioleaching, the concentrations of Mn in exchangeable/acid soluble, reducible and oxidizable forms were reduced by 34.65%, 78.82% and 90.84%, respectively. As for Ni, the removal rates in such forms were 34.66%, 74.58% and 64.99%, respectively. Thus, the higher extraction efficiency of Mn and Ni arose from mixed bioleaching mechanisms, which contain acid dissolution, oxidation and reduction by Fe2+/Fe3+.Relatively low removal efficiency of As (20.78%) was observed in this study. One reason, as shown in Fig. 3, was that As was mainly distributed in residual form with high stability. The other reason was that the dissolved As3+ could be oxidized to As5+ (AsO43-) by Fe3+ generated from the metabolism of iron-oxidizing bacteria, and then insoluble FeAsO4 could be produced through the reaction of AsO43- and Fe3+, which resulted in the reprecipitation of As34.Pb in exchangeable/acid soluble form was not detected in the raw sludge, and mainly existed in reducible (59.20%) and oxidizable (23.19%) forms. The removal rates of Pb in reducible and oxidizable forms were 33.51% and 58.17% after bioleaching, respectively. However, the insoluble compounds such as PbSO4 (Ksp = 1.62 × 10–8) could be generated during the bioleaching process36, which resulted in a significant increase in the concentration of Pb in residual form (from 10.89 to 25.00 mg/kg), and thus led to the low removal ratio of Pb (10.52%).To summarize, the solubilization efficiencies of Zn, Cu, Cd, Mn and Ni, which mainly existed in mobile forms in the raw sludge, were relatively high due to the instability of these metals, while the removal rates of Cr, As and Pb, which mainly existed in immobile forms, were relatively low. However, the contents of most heavy metals in mobile forms decreased obviously after bioleaching and would lead to the corresponding reduction of the environmental risk of the sludge.Combined bioleaching/Fenton-like processEffect of H2O2 dosage on the removal of heavy metals under various pH conditionsPrevious studies have shown that the production ability of hydroxyl radical during the Fenton-like reaction process could be enhanced under pH range of 2.5–4.5, and meanwhile, the amount of H2O2 directly influences the production of hydroxyl radical10,18. Therefore, as shown in Fig. 4, the effects of H2O2 dosage on the solubilization efficiencies of heavy metals were investigated at different stages of the bioleaching process, when the pH values of the bioleached sludge were 4.5 (about 3.5th day), 4.0 (4th day) and 3.0 (6th day).Figure 4Effects of H2O2 dosage on the removal efficiency of heavy metals under various pH conditions.Full size imageWith the increasing concentrations of H2O2 (0.0–8.0 g/L), the solubilization efficiency of Zn increased significantly at pH of 4.5 (Fig. 4) due to the oxidation of metal sulfide and organics by hydroxyl radical10. However, the solubilization percentages of Zn barely changed with further increase of H2O2 dosage (from 8.0 to 15.0 g/L). The solubilization percentage of Zn at the H2O2 dosage of 8.0 g/L (pH of 4.5) was significantly higher than when only using single bioleaching (75.31% vs. 67.64%). The enhancement of solubilization efficiency of Zn at a pH of 4.0 and 3.0 was not very noticeable (Fig. 4), because most of the Zn in immobile forms was dissolved out by bioleaching. The highest solubilization percentages of Zn were 74.96% at a pH of 4.0 and 75.53% at a pH of 3.0, which were 7.32% and 7.89% higher than that of the single bioleaching process.Due to the lower dissolved pH threshold of Cu compared with Zn, the solubilization efficiency of Cu was significantly affected by the dosage of H2O2 at a pH of 4.5 and 4.0 as shown in Fig. 4, while when the reaction pH was 3.0, the subsequent Fenton treatment had a relatively small impact on the removal of Cu. The highest removal rate of Cu (52.17%) was obtained at pH of 3.0 and H2O2 dosage of 13.0 g/L, which was slightly higher than that of the single bioleaching (50.78%). The change in solubilization efficiency of Cd was similar to that of Cu. When the pH values were 4.5 and 4.0, the solubilization percentages of Cd with H2O2 dosage of 15.0 g/L were 4.59% and 1.23% higher than that of the single bioleaching process, respectively. Meanwhile, the highest solubilization percentage of Cd (71.91%) could be reached at a pH of 3.0 and H2O2 dosage of 13.0 g/L, which was higher than that of the single bioleaching process (64.86%).The addition of H2O2 did not increase the removal rate of Cr significantly as shown in Fig. 4. At a reaction pH of 4.5, the solubilization percentage of Cr was 7.59% with H2O2 dosage of 15.0 g/L, which was a little higher than that of the single bioleaching process (6.32%), while the highest solubilization percentages of Cr could reach 11.63% and 9.18% at pH of 4.0 and 3.0, respectively, with H2O2 dosage of 15.0 g/L.The solubilization process of Mn and Ni displayed similar trend as shown in Fig. 4. The solubilization percentage of Mn was not significantly improved when the H2O2 dosage was increased from 5.0 to 11.0 g/L at pH of 4.5 and 4.0, but a much faster increase of the removal rate was observed with the H2O2 dosage over 13.0 g/L. It could be due to the enhanced oxidizing ability of Fenton-like reaction with abundant H2O2. However, the solubilization efficiency of Mn under a pH of 3.0 began to increase with H2O2 concentration of 11.0 g/L, which could be attributed to the high efficiency of Fenton action under lower pH15. The highest removal percentage of Mn was 66.29% at pH of 3.0 and H2O2 dosage of 15.0 g/L, while the removal percentage of Mn in the single bioleaching process was 56.14%. The removal behavior of Ni at various pH was consistent with Mn. The highest removal rate of Ni (65.81%) was found at a pH of 3.0 with H2O2 dosage of 15.0 g/L, which was significantly improved, compared with the single bioleaching process (49.83%).On the contrary, the removal efficiency of As and Pb in the combined process was not promoted compared with the single bioleaching process. Due to the strong oxidizing capacity of Fenton-like process, the yield of SO42− and insoluble FeAsO4 could be improved. Correspondingly, Pb2+ could be transformed into residual form, such as insoluble PbSO410. Therefore, the removal efficiencies of As and Pb decreased in the combined process. The highest removal rates of As and Pb after Fenton-like treatment were 12.46% and 10.20%, respectively.In the combined process, higher solubilization efficiencies of most heavy metals (Zn, Cu, Cd, Mn, Ni, Cr) could be achieved in 6 days. The removal efficiency of heavy metals (except Cr, As and Pb) of combined process (pH of 3.0, H2O2 dosage of 15 g/L) is higher than that of the single bioleaching process. The removal rate of Zn, Cu, Cd, Mn and Ni increased by 7.89%, 0.38%, 5.56%, 10.15% and 15.35%, respectively. Meanwhile, the total concentrations of heavy metals measured in this study after treatment could meet the control standards of pollutants in sludge for agricultural use of China (National Standard GB 4284-2018). The removal of As and Pb was not improved by the combined process, other methods such as chemical leaching, electrokinetic remediation and phytoremediation could be considered as alternatives. However, their transformation into insoluble forms may also reduce the bioavailability of heavy metals and increase the environmental safety of the treated sludge. For that reason, the chemical speciation distributions of heavy metals in the combined process were further analyzed in detail.Chemical fraction distributions of heavy metals in the combined processIt can be seen in Fig. 4 that the solubilization efficiency of most heavy metals did not change significantly with H2O2 dosage below 8.0 g/L. Therefore, the chemical speciation changes of heavy metals after Fenton treatment under H2O2 dosage of 11.0, 13.0 and 15.0 g/L, as shown in Fig. 5, were discussed.Figure 5Change of chemical speciation distributions of heavy metals under different H2O2 dosage at a pH of 4.5, 4.0 and 3.0, total concentration of heavy metal in the raw sludge was set as 100%.Full size imageUnder various pH conditions, the contents of Zn in all of the four forms showed a downward trend along with the increasing H2O2 dosage (Fig. 5). After bioleaching, Zn mainly existed in exchangeable/acid soluble form under the final pH of 4.5 (64.89%), pH of 4.0 (73.33%) and pH of 3.0 (80.82%). The removal of Zn in exchangeable/acid soluble form showed good correlation to the dosage of H2O2, which might be attributed to the destruction of EPS, and the released heavy metals were transferred to the liquid phase. Meanwhile, the improvement of sludge dewaterability could also promote the removal of heavy metals. After Fenton-like reaction at a pH of 4.5, the percentages of Zn in exchangeable/acid soluble forms were reduced by 30.35%, 31.41% and 40.09% at H2O2 dosage of 11.0, 13.0 and 15.0 g/L, respectively, compared with the percentage of Zn in the sludge at the end of the single bioleaching process. However, the percentage of Zn in other forms did not change significantly after Fenton-like treatment. Therefore, the further removal of Zn in exchangeable/acid soluble form and the dewaterability improvement of sludge may be the main reasons for the higher removal efficiency of Zn in the combined process.Cu was still mainly associated with the oxidizable form after bioleaching ended at pH of 4.5, 4.0 and 3.0 (Fig. 5), which might be attributed to the preference of Cu for organic materials22. The addition of H2O2 at pH 4.5 significantly boosted the solubilization efficiency of Cu in exchangeable/acid soluble form. The percentages of Cu in exchangeable/acid soluble form in the sludge after Fenton treatment at pH 4.5 were 24.69% (11.0 g/L), 29.50% (13.0 g/L) and 38.15% (15.0 g/L), which were lower than that at the end of the single bioleaching process. Meanwhile, the content of Cu in reducible form was reduced by nearly 50% with H2O2 dosage of 13.0 and 15.0 g/L, compared with its content after bioleaching ended at pH 4.5. However, the highest removal rate of Cu in oxidizable form was only 33.20% with H2O2 dosage of 15.0 g/L. The removal efficiency of Cu in exchangeable/acid soluble and reducible forms increased with the increasing H2O2 dosage at pH 4.0 and 3.0, similar to the observation at pH 4.5. Under a reaction pH of 4.0, 47.2% of Cu in oxidizable form was removed after Fenton treatment with H2O2 dosage of 13.0 g/L, while only 28.6% was removed at H2O2 dosage of 15.0 g/L. In addition, the removal rates of Cu in oxidizable form were only 4.9–17.7% at various H2O2 dosage at a Fenton reaction pH of 3.0. The removal efficiency of Cu was reduced in despite of the increasing oxidation capacity of Fenton-like reaction. The macro-molecular organic matters could be degraded into small organic molecules during Fenton treatment process, releasing partial Cu. However, the generated small molecule organic matters had more undissociated carboxyl that would combine with released Cu31, which formed Cu in oxidizable form. Thus, it could explain the low removal efficiency of Cu in oxidizable form under stronger oxidizing condition. However, the highest removal rate of Cu (52.17%) was observed at pH 3.0 and H2O2 dosage of 15.0 g/L, due to the high reduction ratio of Cu in mobile forms at that condition.Cd mainly existed in mobile forms in the sludge after bioleaching and Fenton treatment, as shown in Fig. 5. The contents of Cd in mobile and oxidizable forms decreased with the increasing H2O2 dosage at pH 4.5. The content of Cd in exchangeable/acid soluble form after Fenton treatment at pH 4.5 and H2O2 dosage of 15.0 g/L was 29.10% lower than that at the end of the single bioleaching process. Meanwhile, the content of Cd in mobile form was decreased by 27.54% (11.0 g/L), 26.56% (13.0 g/L) and 36.72% (15.0 g/L) after Fenton treatment at pH 4.0. The removal of Cd in exchangeable/acid soluble form after Fenton treatment could be largely due to the improvement of sludge dewaterability. However, the reduction of Cd was not obvious after Fenton treatment at pH 3.0, because the solubilization threshold of most of Cd in various forms were reached after the bioleaching process ended at pH 3.0.The removal efficiency of Cr was not improved obviously by Fenton treatment in this study, as shown in Fig. 5. It was also reported that Cr was difficult to be removed by bioleaching or combined process due to its relatively high stability10. However, the content of Cr in oxidizable form after Fenton treatment at pH 4.5 was 4.76% (11.0 g/L), 9.20% (13.0 g/L) and 9.84% (15.0 g/L) lower than that at the end of the single bioleaching process, due to the strong oxidizing capacity of hydroxyl radical. And the lowest content of Cr in oxidizable form was observed after Fenton treatment at pH 4.0 and H2O2 dosages of 13.0 g/L, which was 39.4% lower than that in the bioleached sludge. Meanwhile, the highest Cr removal rate was also obtained at this condition after Fenton-like treatment. Thus, the improvement of Cr removal in combined process was mainly due to the release of Cr in oxidizable form. Furthermore, the released metals could be absorbed on the surface of oxides31, thus inevitably caused the increase of Cr in reducible form as shown in Fig. 5. The chemical speciation change of Cr after Fenton treatment at pH 3.0 was similar to that at pH 4.0.The removal efficiency and chemical speciation distribution of Mn varied obviously after Fenton treatment with different dosages of H2O2. The removal rate of Mn was improved with the increasing dosage of H2O2 at various pH values. Because most of the Mn in reducible form (over 80%) was removed by bioleaching process, the reduction of Mn in exchangeable/acid soluble form should account for the removal of a substantial part of Mn after Fenton treatment. The highest removal rate of Mn in exchangeable/acid soluble form under different pH conditions was 26.27% (pH 4.5), 25.06% (pH 4.0) and 42.18% (pH 3.0), all with H2O2 dosage of 15.0 g/L. Although nearly 30% of Mn in reducible and oxidizable forms was also removed after Fenton treatment with H2O2 dosage of 15.0 g/L at various pH values, it contributed little to the removal of Mn considering the low concentration of Mn in reducible and oxidizable forms in the raw sludge. Furthermore, the changes of Mn in residual form were not obvious under different pH.The chemical speciation change of Ni was similar to that of Mn after Fenton treatment. The contents of Ni in mobile and oxidizable forms decreased along with the increasing dosage of H2O2, as shown in Fig. 5. Meanwhile, the reduction of Ni in exchangeable/acid soluble form after the addition of H2O2 was the prime reason for the higher removal efficiency of Ni after the combined process than that after the single bioleaching process. The highest removal rate of Ni in exchangeable/acid soluble form was found with H2O2 dosage of 15.0 g/L at pH 4.0, which was 34.47% lower than that in the sludge after the signal bioleaching process. However, the highest removal efficiency of Ni (65.19%) was reached when the reaction pH was 3.0 with H2O2 dosages of 15.0 g/L due to the simultaneous reduction of Ni in reducible and oxidizable forms. The contents of Ni in reducible and oxidizable forms were reduced by 50.30% and 52.83% under this reaction condition, respectively, compared with that at the end of the single bioleaching process.As and Pb were mainly present in residual form before Fenton treatment as shown in Fig. 5. The content of As in exchangeable/acid soluble form decreased significantly due to the degradation of EPS at various pH values with the addition of H2O2. However, the content of As in residual form gradually rose with the increasing dosage of H2O2, probably because As3+ could be oxidized to As5+ by hydroxyl radical and/or Fe3+ with the formation of insoluble FeAsO434. The content of Pb in reducible form showed a trend of increase after Fenton treatment. SO42− was generated due to the oxidation of sulfur elements and/or sulfide in sludge by hydroxyl radicals with the production of insoluble PbSO410, and thus the content of Pb in residual form also increased after further Fenton treatment. Although the Fenton treatment had a negative impact on the removal of As and Pb as shown in Fig. 5, because of the formation of insoluble compounds under strong oxidizing condition, the environmental risk of these two heavy metals decreased to some extent under an appropriate condition, due to the increased proportion of immobile fractions, especially residual form. compared with the bioleached sludge.The content and proportion of most heavy metals (Zn, Cu, Cd, Mn, Ni, As) in mobile forms were lower in the treated sludge after the combined bioleaching and Fenton-like process, compared with the single bioleaching process, which was also the main reason for the high removal efficiency of these metals. Their bioavailability and toxicity were also reduced. However, Fenton treatment was found to have a negative impact on the removal of As, but the increased proportion of As in residual form also lowered its bioavailability and mobility in the environment. The increase in the content of Pb in both mobile forms (mainly in reducible form) and immobile forms (mainly in residual form) was observed under different conditions, so special attention should be paid to the chemical speciation distributions of Pb during sludge treatment process.The effect of H2O2 dosage on sludge dewaterability at different pH valuesThe changes of CST of treated sludge under various conditions are presented in Fig. 6. The CST of the raw sludge (98.7 s) was dramatically reduced by bioleaching and Fenton oxidation treatments. After bioleaching ended on the 10th day (pH 2.89), the 6th day (pH 3.0), the 4th day (4.0) and the 3.5th day (pH 4.5), CST values of 20.3 s, 24.2 s, 30.7 s and 35.0 s were observed. The decreased pH after bioleaching process could destroy the EPS and neutralize the negative charge of the sludge flocs, resulting in the release of bound water37. Moreover, sludge dewatering could also be improved by the coagulation effect of Fe2+ 10. Furthermore, hydroxyl radicals were essential to improve sludge dewatering performance by destroying EPS and porous structure during the Fenton treatment process35. Therefore, the CST value of treated sludge was reduced to 20.6 s after Fenton treatment with H2O2 dosage of 15 g/L at pH 4.5, which was comparable to the CST value at the end of the single bioleaching process. The CST values were further reduced along with the decreasing reaction pH (4.0 and 3.0) and the increasing H2O2 dosage. The lowest CST value of 12.4 s was observed at Fenton reaction pH 3.0 and H2O2 dosage of 15.0 g/L, which meant a reduction from the initial CST of 87.44%. Therefore, the combined process could lead to an obvious improvement of the sludge dewaterability and significantly reduced the treatment period.Figure 6Changes of CST under different H2O2 dosage and pH.Full size image More

1.Cardinale, B. J. et al. Biodiversity loss and its impact on humanity. Nature 486, 59–67 (2012).ADS 
CAS 
PubMed 
Article 

Google Scholar 
2.Hooper, D. U. et al. Effects of biodiversity on ecosystem functioning: a consensus of current knowledge. Ecol. Monogr. 75, 3–35 (2005).Article 

Google Scholar 
3.Isbell, F. et al. Linking the influence and dependence of people on biodiversity across scales. Nature 546, 65–72 (2017).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
4.Loreau, M. & Hector, A. Partitioning selection and complementarity in biodiversity experiments. Nature 412, 72–76 (2001).ADS 
CAS 
PubMed 
Article 

Google Scholar 
5.Bessler, H. et al. Nitrogen uptake by grassland communities: contribution of N2 fixation, facilitation, complementarity, and species dominance. Plant Soil 358, 301–322 (2012).CAS 
Article 

Google Scholar 
6.Karanika, E. D., Alifragis, D. A., Mamolos, A. P. & Veresoglou, D. S. Differentiation between responses of primary productivity and phosphorus exploitation to species richness. Plant Soil 297, 69–81 (2007).CAS 
Article 

Google Scholar 
7.Lange, M. et al. How plant diversity impacts the coupled water, nutrient and carbon cycles. Adv. Ecol. Res. 61, 185–219 (2019).Article 

Google Scholar 
8.Oelmann, Y. et al. Does plant diversity influence phosphorus cycling in experimental grasslands? Geoderma 167-68, 178–187 (2011).ADS 
Article 
CAS 

Google Scholar 
9.Tilman, D., Wedin, D. & Knops, J. Productivity and sustainability influenced by biodiversity in grassland ecosystems. Nature 379, 718–720 (1996).ADS 
CAS 
Article 

Google Scholar 
10.Leimer, S., Oelmann, Y., Wirth, C. & Wilcke, W. Time matters for plant diversity effects on nitrate leaching from temperate grassland. Agric Ecosyst. Environ. 211, 155–163 (2015).CAS 
Article 

Google Scholar 
11.Scherer-Lorenzen, M., Palmborg, C., Prinz, A. & Schulze, E.-D. The role of plant diversity and composition for nitrate leaching in grasslands. Ecology 84, 1539–1552 (2003).Article 

Google Scholar 
12.Elser, J. & Bennett, E. A broken biogeochemical cycle. Nature 478, 29–31 (2011).ADS 
CAS 
PubMed 
Article 

Google Scholar 
13.Lambers, H., Mougel, C., Jaillard, B. & Hinsinger, P. Plant-microbe-soil interactions in the rhizosphere: an evolutionary perspective. Plant Soil 321, 83–115 (2009).CAS 
Article 

Google Scholar 
14.Wassen, M. J., Olde Venterink, H., Lapshina, E. D. & Tanneberger, F. Endangered plants persist under phosphorus limitation. Nature 437, 547–550 (2005).ADS 
CAS 
PubMed 
Article 

Google Scholar 
15.Cordell, D., Drangert, J.-O. & White, S. The story of phosphorus: Global food security and food for thought. Glob. Environ. Change-Hum. Policy Dimens. 19, 292–305 (2009).Article 

Google Scholar 
16.van der Heijden, M. G. A., Martin, F. M., Selosse, M.-A. & Sanders, I. R. Mycorrhizal ecology and evolution: the past, the present, and the future. N. Phytol. 205, 1406–1423 (2015).Article 
CAS 

Google Scholar 
17.van der Heijden, M. G. A. et al. Mycorrhizal fungal diversity determines plant biodiversity, ecosystem variability and productivity. Nature 396, 69–72 (1998).ADS 
Article 
CAS 

Google Scholar 
18.Richardson, A. E. & Simpson, R. J. Soil microorganisms mediating phosphorus availability. Plant Physiol. 156, 989–996 (2011).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
19.Hacker, N. et al. Plant diversity shapes microbe-rhizosphere effects on P mobilisation from organic matter in soil. Ecol. Lett. 18, 1356–1365 (2015).PubMed 
Article 

Google Scholar 
20.Hacker, N., Wilcke, W. & Oelmann, Y. The oxygen isotope composition of bioavailable phosphate in soil reflects the oxygen isotope composition in soil water driven by plant diversity effects on evaporation. Geochim. Cosmochim. Acta 248, 387–399 (2019).ADS 
CAS 
Article 

Google Scholar 
21.Craven, D. et al. Plant diversity effects on grassland productivity are robust to both nutrient enrichment and drought. Philos. Trans. R. Soc. B 371, 8 (2016).Article 

Google Scholar 
22.Fridley, J. D. Resource availability dominates and alters the relationship between species diversity and ecosystem productivity in experimental plant communities. Oecologia 132, 271–277 (2002).ADS 
PubMed 
Article 

Google Scholar 
23.Weigelt, A., Weisser, W. W., Buchmann, N. & Scherer-Lorenzen, M. Biodiversity for multifunctional grasslands: equal productivity in high-diversity low-input and low-diversity high-input systems. Biogeosciences 6, 1695–1706 (2009).ADS 
CAS 
Article 

Google Scholar 
24.Nyfeler, D. et al. Strong mixture effects among four species in fertilized agricultural grassland led to persistent and consistent transgressive overyielding. J. Appl Ecol. 46, 683–691 (2009).Article 

Google Scholar 
25.Oelmann, Y., Vogel, A., Wegener, F., Weigelt, A. & Scherer-Lorenzen, M. Management intensity modifies plant diversity effects on N yield and mineral N in soil. Soil Sci. Soc. Am. J. 79, 559–568 (2015).ADS 
CAS 
Article 

Google Scholar 
26.Manning P., et al. Transferring biodiversity-ecosystem function research to the management of ‘real-world’ ecosystems. In: Mechanisms Underlying the Relationship between Biodiversity and Ecosystem Function (ed^(eds Eisenhauer N., Bohan D. A., Dumbrell A. J.). Academic Press Ltd-Elsevier Science Ltd (2019).27.Kraft, N. J. B. et al. Community assembly, coexistence and the environmental filtering metaphor. Funct. Ecol. 29, 592–599 (2015).Article 

Google Scholar 
28.Allan, E. et al. Land use intensification alters ecosystem multifunctionality via loss of biodiversity and changes to functional composition. Ecol. Lett. 18, 834–843 (2015).PubMed 
PubMed Central 
Article 

Google Scholar 
29.Collins, C. D. & Foster, B. L. Community-level consequences of mycorrhizae depend on phosphorus availability. Ecology 90, 2567–2576 (2009).PubMed 
Article 

Google Scholar 
30.Klironomos, J. N., McCune, J., Hart, M. & Neville, J. The influence of arbuscular mycorrhizae on the relationship between plant diversity and productivity. Ecol. Lett. 3, 137–141 (2000).Article 

Google Scholar 
31.Busch, V. et al. Will I stay or will I go? Plant species-specific response and tolerance to high land-use intensity in temperate grassland ecosystems. J. Veg. Sci. 30, 674–686 (2019).Article 

Google Scholar 
32.Sorkau, E. et al. The role of soil chemical properties, land use and plant diversity for microbial phosphorus in forest and grassland soils. J. Plant Nutr. Soil Sci. 181, 185–197 (2018).CAS 
Article 

Google Scholar 
33.Wardle, D. A. A comparative assessment of factors which influence microbial biomass carbon and nitrogen levels in soil. Biol. Rev. Camb. Philos. Soc. 67, 321–358 (1992).Article 

Google Scholar 
34.Lange, M. et al. Plant diversity increases soil microbial activity and soil carbon storage. Nat. Commun. 6, 6707 (2015).ADS 
CAS 
PubMed 
Article 

Google Scholar 
35.Eisenhauer, N. et al. Plant diversity effects on soil microorganisms support the singular hypothesis. Ecology 91, 485–496 (2010).CAS 
PubMed 
Article 

Google Scholar 
36.Cleveland, C. C. & Liptzin, D. C. N: P stoichiometry in soil: is there a “Redfield ratio” for the microbial biomass? Biogeochemistry 85, 235–252 (2007).Article 

Google Scholar 
37.Cardinale, B. J. et al. Impacts of plant diversity on biomass production increase through time because of species complementarity. Proc. Natl Acad. Sci. USA 104, 18123–18128 (2007).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
38.Marquard, E. et al. Plant species richness and functional composition drive overyielding in a 6-year grassland experiment. Ecology 90, 3290–3302 (2009).PubMed 
Article 

Google Scholar 
39.Liebisch, F. et al. Seasonal dynamics and turnover of microbial phosphorus in a permanent grassland. Biol. Fertil. Soils 50, 465–475 (2014).CAS 
Article 

Google Scholar 
40.Boeddinghaus, R. S. et al. Plant functional trait shifts explain concurrent changes in the structure and function of grassland soil microbial communities. J. Ecol. 107, 2197–2210 (2019).CAS 
Article 

Google Scholar 
41.Soussana, J. F. et al. Carbon cycling and sequestration opportunities in temperate grasslands. Soil Use Manag. 20, 219–230 (2004).Article 

Google Scholar 
42.Waldrop, M. P., Zak, D. R., Blackwood, C. B., Curtis, C. D. & Tilman, D. Resource availability controls fungal diversity across a plant diversity gradient. Ecol. Lett. 9, 1127–1135 (2006).PubMed 
Article 

Google Scholar 
43.Kour, D. et al. Biodiversity, current developments and potential biotechnological applications of phosphorus-solubilizing and -mobilizing microbes: a review. Pedosphere 31, 43–75 (2021).Article 

Google Scholar 
44.Dijkstra, F. A., He, M. Z., Johansen, M. P., Harrison, J. J. & Keitel, C. Plant and microbial uptake of nitrogen and phosphorus affected by drought using N-15 and P-32 tracers. Soil Biol. Biochem. 82, 135–142 (2015).CAS 
Article 

Google Scholar 
45.Hiiesalu, I. et al. Species richness of arbuscular mycorrhizal fungi: associations with grassland plant richness and biomass. N. Phytol. 203, 233–244 (2014).CAS 
Article 

Google Scholar 
46.Tilman, D., Cassman, K. G., Matson, P. A., Naylor, R. & Polasky, S. Agricultural sustainability and intensive production practices. Nature 418, 671–677 (2002).ADS 
CAS 
PubMed 
Article 

Google Scholar 
47.Roscher, C. et al. The role of biodiversity for element cycling and trophic interactions: an experimental approach in a grassland community. Bas Appl. Ecol. 5, 107–121 (2004).Article 

Google Scholar 
48.Hoffmann K., Bivour W., Früh B., Koßmann M., Voß P.-H. Climate studies in Jena for adaption to climate change and ist expected consequences. (In German). Selbstverlag des Deutschen Wetterdienstes (2014).49.IUSS Working Group WRB. World Reference Base for Soil Resources 2014, update 2015: International soil classification system for naming soils and creating legends for soil maps. FAO (2015).50.Fischer, M. et al. Implementing large-scale and long-term functional biodiversity research: the biodiversity exploratories. Bas Appl Ecol. 11, 473–485 (2010).Article 

Google Scholar 
51.Alt, F., Oelmann, Y., Herold, N., Schrumpf, M. & Wilcke, W. Phosphorus partitioning in grassland and forest soils of Germany as related to land-use type, management intensity, and land use-related pH. J. Plant Nutr. Soil Sci. 174, 195–209 (2011).CAS 
Article 

Google Scholar 
52.Vogt, J. et al. Eleven years’ data of grassland management in Germany. Biodiver Data J. 7, 38 (2019).Article 

Google Scholar 
53.Alt, F., Oelmann, Y., Schöning, I. & Wilcke, W. Phosphate release kinetics at stable pH in calcareous grassland and forest soils. Soil Sci. Soc. Am. J. 77, 2060–2070 (2013).ADS 
CAS 
Article 

Google Scholar 
54.Jones J. B., Wolf B., Mills H. A. Plant analysis handbook. Micro Macro Publishing (1991).55.Marina, M. A. & Lopez, M. C. B. Determination of phosphorus in raw materials for ceramics: comparison between X-ray fluorescence spectrometry and inductively coupled plasma-atomic emission spectrometry. Anal. Chim. Acta 432, 157–163 (2001).CAS 
Article 

Google Scholar 
56.Hedley, M. J., Stewart, J. W. B. & Chauhan, B. S. Changes in inorganic and organic soil-phosphorus fractions induced by cultivation practices and by laboratory incubations. Soil Sci. Soc. Am. J. 46, 970–976 (1982).ADS 
CAS 
Article 

Google Scholar 
57.Kuo S. Phosphorus. In: Methods of Soil Analysis – Part 3 Chemical Methods (eds Sparks D. L., et al.). SSSA (1996).58.Cross, A. F. & Schlesinger, W. H. A literature review and evaluation of the Hedley fractionation – applications to the biogeochemical cycle of soil phosphorus in natural ecosystems. Geoderma 64, 197–214 (1995).ADS 
CAS 
Article 

Google Scholar 
59.Negassa, W. & Leinweber, P. How does the Hedley sequential phosphorus fractionation reflect impacts of land use and management on soil phosphorus: a review. J. Plant Nutr. Soil Sci. 172, 305–325 (2009).CAS 
Article 

Google Scholar 
60.Murphy, J. & Riley, J. P. A modified single solution method for determination of phosphate in natural waters. Anal. Chim. Acta 26, 31–36 (1962).Article 

Google Scholar 
61.McLaughlin, M. J., Alston, A. M. & Martin, J. K. Measurement of phosphorus in the soil microbial biomass – a modified procedure for field soils. Soil Biol. Biochem. 18, 437–443 (1986).CAS 
Article 

Google Scholar 
62.Kouno, K., Tuchiya, Y. & Ando, T. Measurement of soil microbial biomass phosphorus by an anion exchange membrane method. Soil Biol. Biochem. 27, 1353–1357 (1995).CAS 
Article 

Google Scholar 
63.Bünemann, E. K., Marschner, P., Smernik, R. J., Conyers, M. & McNeill, A. M. Soil organic phosphorus and microbial community composition as affected by 26 years of different management strategies. Biol. Fertil. Soils 44, 717–726 (2008).Article 

Google Scholar 
64.Brookes, P. C., Powlson, D. S. & Jenkinson, D. S. Measurement of microbial biomass phosphorus in soil. Soil Biol. Biochem 14, 319–329 (1982).CAS 
Article 

Google Scholar 
65.Eivazi, F. & Tabatabai, M. A. Phosphatases in soils. Soil Biol. Biochem. 9, 167–172 (1977).CAS 
Article 

Google Scholar 
66.Marx, M. C., Wood, M. & Jarvis, S. C. A microplate fluorimetric assay for the study of enzyme diversity in soils. Soil Biol. Biochem. 33, 1633–1640 (2001).CAS 
Article 

Google Scholar 
67.Berner, D. et al. Land-use intensity modifies spatial distribution and function of soil microorganisms in grasslands. Pedobiologia 54, 341–351 (2011).ADS 
Article 

Google Scholar 
68.White, D. C., Davis, W. M., Nickels, J. S., King, J. D. & Bobbie, R. J. Determination of the sedimentary microbial biomass by extractable lipid phosphate. Oecologia 40, 51–62 (1979).ADS 
CAS 
PubMed 
Article 

Google Scholar 
69.Bligh, E. G. & Dyer, W. J. A rapid method of total lipid extraction and purification. Can. J. Biochem. Physiol. 37, 911–917 (1959).CAS 
PubMed 
Article 

Google Scholar 
70.Kramer, C. & Gleixner, G. Variable use of plant- and soil-derived carbon by microorganisms in agricultural soils. Soil Biol. Biochem. 38, 3267–3278 (2006).CAS 
Article 

Google Scholar 
71.Frostegard, A. & Baath, E. The use of phospholipid fatty acid analysis to estimate bacterial and fungal biomass in soil. Biol. Fertil. Soils 22, 59–65 (1996).Article 

Google Scholar 
72.Zelles, L. Identification of single cultured micro-organisms based on their whole-community fatty acid profiles, using an extended extraction procedure. Chemosphere 39, 665–682 (1999).ADS 
CAS 
PubMed 
Article 

Google Scholar 
73.Dassen, S. et al. Differential responses of soil bacteria, fungi, archaea and protists to plant species richness and plant functional group identity. Mol. Ecol. 26, 4085–4098 (2017).CAS 
PubMed 
Article 

Google Scholar 
74.Kuramae, E. E. et al. Tracking fungal community responses to maize plants by DNA- and RNA-based pyrosequencing. PLoS ONE 8, 8 (2013).Article 
CAS 

Google Scholar 
75.Wubet, T., Weiss, M., Kottke, I. & Oberwinkler, F. Two threatened coexisting indigenous conifer species in the dry Afromontane forests of Ethiopia are associated with distinct arbuscular mycorrhizal fungal communities. Can. J. Bot.-Rev. Canadienne De. Botanique 84, 1617–1627 (2006).CAS 

Google Scholar 
76.Lee, J., Lee, S. & Young, J. P. W. Improved PCR primers for the detection and identification of arbuscular mycorrhizal fungi. FEMS Microbiol. Ecol. 65, 339–349 (2008).CAS 
PubMed 
Article 

Google Scholar 
77.Simon, L., Lalonde, M. & Bruns, T. D. Specific amplification of 18S fungal ribosomal genes from vesicular-arbuscular endomycorrhizal fungi colonizing roots. Appl. Environ. Microbiol. 58, 291–295 (1992).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
78.Lefcheck, J. S. PIECEWISESEM: Piecewise structural equation modelling in R for ecology, evolution, and systematics. Methods Ecol. Evol. 7, 573–579 (2016).Article 

Google Scholar 
79.van der Heijden, M. G. A. et al. The mycorrhizal contribution to plant productivity, plant nutrition and soil structure in experimental grassland. N. Phytol. 172, 739–752 (2006).Article 

Google Scholar 
80.Frew, A. Arbuscular mycorrhizal fungal diversity increases growth and phosphorus uptake in C-3 and C-4 crop plants. Soil Biol. Biochem. 135, 248–250 (2019).CAS 
Article 

Google Scholar 
81.Hedlund, K. et al. Plant species diversity, plant biomass and responses of the soil community on abandoned land across Europe: idiosyncracy or above-belowground time lags. Oikos 103, 45–58 (2003).Article 

Google Scholar 
82.Treseder, K. K. The extent of mycorrhizal colonization of roots and its influence on plant growth and phosphorus content. Plant Soil 371, 1–13 (2013).CAS 
Article 

Google Scholar 
83.Köhl, L., Oehl, F. & van der Heijden, M. G. A. Agricultural practices indirectly influence plant productivity and ecosystem services through effects on soil biota. Ecol. Appl. 24, 1842–1853 (2014).PubMed 
Article 

Google Scholar 
84.Fornara, D. A. & Tilman, D. Plant functional composition influences rates of soil carbon and nitrogen accumulation. J. Ecol. 96, 314–322 (2008).CAS 
Article 

Google Scholar 
85.Steinbeiss, S. et al. Plant diversity positively affects short-term soil carbon storage in experimental grasslands. Glob. Change Biol. 14, 2937–2949 (2008).ADS 
Article 

Google Scholar 
86.Hacker N. Phosphorus Release Mechanisms in an Experimental Grassland of Varying Biodiversity. Doctoral thesis, University of Tübingen, Germany (2017). More

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain
the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in
Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles
and JavaScript. More