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Landscape use and anthropogenic influenceThe site could have had a specific and maybe extraordinary position in the microregion or in the trade networks41,42. The idea for creating trenches may have spread along trade routes—either as a habit of migrating people or as an ideology in the area of South and West Bohemia, Southern Germany, and the Austrian Land Salzburg55,56,57.Creeks along the settlement were major landscape elements. The settlement itself is entirely situated in the landscape periphery2. Steep slopes above Židova strouha creek and Blatenský potok brooks fundamentally limit agricultural use of the hinterland on the Březnice site, based on a model of reconstruction of the landscape potential (Fig. 6). The slopes may have been covered with sparse forest or shrubs. They were also forested in the nineteenth century, at the time of maximum agricultural load on the landscape as historical maps prove (Fig. 7).Figure 7Březnice and Hvožďany: the map of the second military mapping. Site catchements81 are according to the walk distance83 are shown hatched.Full size imageFieldsIn terms of human nutrition, the fields were crucial. The arable field area consisted of the actually cultivated fields and fallows. Analysis of plant macroremains provides us with knowledge of the grown species and the weed spectrum. The potential area and location of fields are reconstructed by a model that combines the agricultural potential of the landscape and previously published knowledge of the economic needs of the economic unit2,5,60,61,62,63.There is a possibility to assume, according to the SCA, the location of fields in relatively drier parts of the settlement area. Areas suitable for fields were probably located eastward and northward of the site, about 10–15 min walking distance (Fig. 6). The burial site was located beyond the northern border of the area where our analysis predicted the existence of fields93.Areas located eastward and northward of the settlement are even drier nowadays. The wetter fields may have been located in the north and northeast of the settlement, in its immediate vicinity. Moist soil is still present in these places today. The seeds and fruits of weed plants appear to have been transferred into the settlement together with the harvest. After being cleaned they were deposited as waste or used for further purposes, e.g. as an organic ingredient in ceramics or in daub4. The drier fields could correspond to finds of the following plant species: Arenaria serpyllifolia, Clinopodium acinos, Galeopsis augustifolia, Geranium cf. columbinum, Medicago lupulina, Rumex acetosella, Scleranthus annuus. Conversely, the following plants may have grown in the wetter fields, as documented in features on the settlement: Echinochloa crus-galli, Fumaria officinalis, Persicaria lapatifolia, Rumex cf. acetosa, Stachys arvensis.Synanthropic vegetation and ruderal habitatsArchaeobotanical analysis recorded many plant species characteristic for ruderal vegetation (most frequented Chenopodium album, Atriplex sp., Galium spurium, Polygonum aviculare, Chenopodium ficifolium, Fallopia convolvulus, Galium aparine). One could expect the presence of ruderals in the settlement area and its nearest surroundings in places that have been intensively used by humans and animals. The plants on the site could have reached the buildings by direct sedimentation and accidental charring, use of the ruderal plants, or as a result of waste burning.Deforested grazing areasGrazing took place in the enclosures and in the forests, which were made more open. The grazing of domestic animals had to be regulated in order to avoid crop damage and free movement around the settlement area. Winter fodder for animals had to be obtained within the reach of the settlement area, which contributed to the further lowering density of the forest. The archaeobotanical data reflect the grazing habitats in forest and deforested areas. Detrended correspondence analysis shows two clusters of plant species compatible with such environment (Fig. 4). The question is the process by which the plants reached the settlements. Species which appear in the ordinary space between the grassland and woodland—shrub positions could have grown on grasslands and light forests (e.g. Lychnis flos-cuculi, Dianthus cf. armeria, Galium palustre, Festuca ovina, Juncus sp., Campanula cf. glomerata) species in the ordinary space between “ruderal” and “grassland” could have grown at both habitats, e.g. at the transition of the settlement to the open countryside (e.g. Achillea millefolium, Alopecurus pratense, Asperula cynanchica, Briza media, Festuca cf. pratensis, Galium cf. verum, Ranunculus cf. bulbosus, Silene vulgaris, Stellaria graminea, Trifolium pratense). Taxa displayed between the “field” and “grassland” could have grown for example on fallow lands or abandoned fields that have successively overgrown (e.g. Clinopodinum acinus, Plantago lanceolata, Trifolium repens, Polycnemum arvense, Trifolium arvense). Taxa typical for “field” and “woodland-shrub” significantly differ in Březnice (Fig. 8).Figure 8Březnice: detrended correspondence analysis (DCA) Displayed samples and botanical taxa: the first axis explains 44.57% variability, the first and the second axis together 50.47%.Full size imageThe archaeobotanical analysis captured multiple grassland types. Both drier and wetter environments can be reconstructed. Wetter areas were represented by e.g. Alopecurus pratense, Alopecurus geniculatus, Carex cf. hirta, Carex cf. vulpina, cf. Euphorbia palustris, Galium cf. palustre, Juncus sp., Lychnis flos-cuculi, Myosotis sp., Persicaria lapatifolia, Plantago lanceolata, Stachys cf. palustris, Stellaria graminea, Urtica dioica. Drier areas were represented by e.g. Asperula cynanchica, Briza media, Campanula cf. glomerata, Carex cf. contigua, Clinopodium acinos, Dianthus cf. armeria, Phleum sp., Festuca cf. ovina, Galeopsis augustifolia, Galium cf. verum, Medicago lupulina, Polycnemum arvense, Ranunculus cf. bulbosus, Scleranthus annuus, Silene vulgaris, Solanum nigrum, Spergula arvensis, Trifolium arvense, Vicia tetrasperma, Vicia cf. villosa (Fig. 8).The existence of grasslands is associated with long-term human activities94. The Bechyně region has been apparently continuously settled since the end of the Early Bronze Age34. The landscape around the settlements has always been influenced by human activity and a large part of it has been deforested or covered with a sparse pastoral forest. However, not all the settlement areas were occupied permanently3, and those which were unoccupied became overgrown.Meadows and pastures are much more suitable for the grazing of herbivores than a forest with a dense canopy. Forest-steppe or significantly open forest is a convenient combination ensuring sufficient grazing for animals and wood production. Grazing increased soil fertility, reduced weeds on ruderal sites, and prevented forest growth95. Our study recorded a wide spectrum of charred macroremains of plants, which grew in the grasslands. They could have reached the site in several ways. In the excrements of the animals coming from a grazing area96, as raw materials collected by humans for further use in the settlement economy (e.g. food, medicinal plants, dyeing plants, bedding, admixture of screed and ceramic earth and daub, etc.). Studies1,3,32 assume, that the area in the immediate vicinity of the site was probably forestless. Forests at least half an hour’s walking distance from the site was significantly influenced by human activity. With an increasing distance from the centre of the site, the forest was probably less affected by human activities. The character of woodland usually clearly corresponded with the environmental conditions of the location31. The current forest area is extremely unsuitable for usage (slopes, wetlands). We assume that the occurrence of woodlands and shrubs in the Late Bronze Age was much more widespread, even in less extreme habitats.Shrubs and forestSpecies of herbs from different forest and shrub environments were also frequently recorded in the archaeobotanical assemblage. In the environment of wet forests could have grown e.g. Alliaria petiolata, Galium cf. palustre, Galium odoratum, Galium sylvaticum, Lychnis flos-cuculi, Persicaria lapatifolia, Solanum dulcamara, Stachys cf. palustris. In the coastal shrubs and edges of wet forests could have occured e.g. Cuscuta cf. europea, cf. Euphorbia palustris, Chelidinium majus, Impatiens nolitangere, Juncus sp., Myosoton aquaticum, Urtica dioica, Veronica hederifolia. Suitable locations could have been along the streams that flowed around the settlement and were within a quarter-hour walk. On the edges of the forests and their glades could have grown e.g. Atropa bella-donna, Festuca cf. ovina, Galium aparine, Prunella vulgaris, Rumex acetosella, Silene dioica, Thymus sp. Light forests and slopes were suitable for e.g. for Campanula cf. glomerata, Carex cf. contigua, Dianthus cf. armeria, Geranium cf. columbinum (Fig. 8).The areas for hunting and harvesting of wild crops were also economically important. The fruits that could have been collected included Corylus avellana, Crataegus sp., Atropa bella-donna, Prunus spinosa, Quercus sp., Rubus ideaus, Rubus fruticosus, Sambucus nigra, Solanum nigrum, Solanum dulcamara; their remains were found in the infills of features. The source of the collected fruits was located mostly in the sparse forest, forest edges and shrubs.The forest was also a source of building material and firewood3. From this acreage, the firewood for one farm could have been collected from 10 hectares. The rest would be used for collecting fodder and forest grazing7. The map of the potential natural vegetation92 predicts acidophilous oak forests (Quercetea robori-petraeae, Fig. 7) for the majority of both settlement areas. These species-poor woodlands are characteristic of Quercus dominance and in places mixed with Betula, Pinus, Sorbus, and Tilia on both dry and wet acidic soils, and Fagus, Abies, or Picea at higher altitudes. The results of our anthracological analysis clearly documented the predominance of this vegetation type in the vicinity of both archaeological sites.In the valleys of the streams and rivers were reconstructed alluvial forests with Alnus and mesophilous oak-hornbeam woods. The archeobotanical analysis of charcoals and fragments of fruits detected presence of Quercus, Tilia, Corylus, Crataegus, and Carpinus. These macroremains indicate existence of mesophilous forests. The hornbeam is rare in southern Bohemia97, it is the first of the archaeobotanical finds from prehistory. Due to the structure of taxa, which was captured by archaeobotanical analysis in Březnice, meadows and alder tree woods may be assumed there. Results of archaeobotanical analysis also documented the presence of Salix/Populus, Alnus.The most dominant tree species discovered in the trench-like features was oak which was mainly used as a construction material (Fig. 5). Firs were used as construction wood, which is predominantly present in stake pits in Březnice. In Hvožďany, trench 1 contained a cultural layer with apparent remains of a destructed building with charcoals of fir, spruce, and pine which in this case also served as construction wood34. The material commonly available in the forests surrounding the settlement area served as firewood (Figs. 4, 5, 8, 9).Figure 9Hvožďany: detrended correspondence analysis (DCA) Displayed samples and botanical taxa: the first axis explains 64.08% variability, the first and the second axis together 72.12%.Full size imageTime of housing: landscape potential vs. human needsThe homestead management (construction, abandonment, destruction, reconstruction etc.) during the settlement´s lifespan is a long-term studied question98,99. The existence of a hierarchized Late Bronze Age settlement network was evident in the lowland settlement areas of the Czech Republic with the continuity of occupational activity. Two main types of settlement are usually recognized there: (1) long-term large settlements and (2) short-term small settlements100,101. Agricultural productivity, exploitation of natural resources in settlements areas, and trade networks differed in cases of small or large settlements102. From the archaeological evidence perspective, the South Bohemia region was sparsely populated and the presence of long-term large settlements areas was very rare34.Previous research (excavations and magnetometry survey) has led to the conclusion that the 70 trenches are depositions of 70 houses and each trench is a deposition of one original house4,5,58. Based on such data, there could be many settlement forms differing in the space and time. The possible size of the settlement could be derived from the comparison of demands for fields, pastures, and forests with carrying capacity.SCA model and prediction model when compared to the possible demand7 of the community show that forest and pastures were not limiting factor for the settlement sustainability. In case of fields, there could be four variants of the possible extent of the settlement connected with different intensity of landuse. (1) The optimal acreage of fields (69 ha) with optimal land-use (7.5 ha/household); (2) the maximal extent of the fields 104 ha with optimal land-use or optimal extent of the field systems with intensive land-use (5 ha); (3) the maximal extent of the fields 104 ha and intensive land-use (5 ha); (4) sub-optimal land-use and fields located outside of the reach and optimal soils (Table 2). This model is an ideal prediction. For better yield the farmer could travel longer time than is expected however poor soils on a sloped terrain in the close vicinity were probably used rather as pastures.Table 2 Březnice: possible duration of the settlement based on four land use strategies: light green-optimal extent of the fields (69 hectares), with 7.5 hectares of fields per homestead; dark green-maximal extent of the fields (104 ha) or more intensive use of the fields (5 ha/homestead); maximal use and maximal extent; red—not sustainable agriculture or location of fields on places outside predicted optimal areas.Full size tableDrawing upon the typological and radiocarbon dating, it is often impossible to find out what was the lifespan of the settlement on the actual site. In this case, the uncertainty of 14C dates gives us a maximum possible span 73–264 years (95% probability), probably for 107–192 years (68% probability) (Supplementary Table 1, Fig. 2). Typological dating indicates 100–150 years (1150–1000 BC).The model described above indicates that the hinterland of Březnice could have sustained up to 20 houses at the same time in case of the maximal extent of the fields and intensive land-use. In this case, the settlement would have lasted only 90 years. If the land was used extensively it could have bore maximum of 14 houses at the time. That would correspond to a duration of roughly 126 years. Optimal areas of field systems in combination with sufficiently large fallows could have been used by a maximum of nine houses present at the time (192 years). The crucial part of the model is ritual burning and rebuilding houses after one generation58.Models of potential spatial and temporal characteristics of the settlement derived from prediction modeling cannot be tested. Therefore we need to compare our predictions with the radiocarbon model. The shortest duration of the settlement based on prediction is 90 years which corresponds with the 72 years modelled from 14C data. Since the model does not reflect the maximal duration of dwelling, this limit has to be based only on 14C model (262 years at 95% probability. At the maximum possible landuse levels, the settlement could have lasted from 72/90 to 262 years. The optimal duration of the settlement based on prediction could be 192–262 years. Extensive but more demanding land-use could support the duration of the settlement from 126 to 262 years (Table 2).Březnice and Hvožďany: the interpretation of both settlement areas from an archaeobotanical perspectiveThe two similarly dated settlement areas in one microregion with high quality archaeobotanical data allow (based on archaeobotanical material) a detailed study of the behaviour of communities in the Late Bronze Age. Archaeobotanical assemblages bring the reconstruction of the environment where the communities of the settlements drew plant resources from. Although the number of plant remains from both sites is significantly different, the interpretation of the environment does not differ in broad terms. For both sites, a similar share of fields and ruderals was documented. The spectrum of cultivated species was also identical41. Both settlements were self-sufficient in plant production—both waste and production parts of cultivated plants were found in the assemblages21,34,41. Animal bones were not preserved due to the acidic soil. However, for the Late Bronze Age sites the types of the domestic103 and the hunted104 animals are known.According to the environmental model, a greater proportion of species in Březnice came from grassland rather than from woodland and shrubs (Fig. 4). According to the analysis of plant macroremains more deforestation was recorded (i.e. more fields and pastures) in Březnice than in Hvožďany (Figs. 4, 5, 8, 9). Predicted areas for fields were in case of Hvožďany from 27 to 130 ha. Hvožďany site could possibly have larger field systems, but further away than in case of Březnice settlement. In Hvožďany there have been documented many taxa typical also for ruderal sites and fields. Several taxa could have grown either on ruderal sites or grasslands. Three reconstructed environments (ruderals, fields, grasslands) in Hvožďany significantly differ from woodland—shrub (Figs. 8, 9). The large volume of analysed samples from Březnice brought a number of botanical taxa which was mostly found in only a few specimens but ultimately brought the opportunity to reconstruct the surroundings of the site in more detail. In Hvožďany, a common spectrum of plants was found (Fig. 9), which usually occurs at similar South Bohemian sites, e.g. Černýšovice, Rataje, Zhoř, Oldřichov, Písek—Bakaláře105,106. Nevertheless, it brings the possibility to reconstruct the surroundings at least in rough features.The archaeological field data does not allow us to reconstruct how many houses were on the Hvožďany site at the same time. Total inhabited area of ​​the settlement in Březnice is approximately 13 ha, at Hvožďany site it is altogether 5 ha. It suggests two explanations: either more people lived in Březnice than in Hvožďany or the settlement had a longer span (or both possibilities). However, both options mean greater deforestation in Březnice. The carrying capacity and landscape potential of the settlement in Hvožďany could not have been exhausted (Fig. 6). The area of high quality soil in a quarter/half hour’s walk from the site is sufficient for 3.6–25 houses (27–130 ha). Two community areas could have been separated by the Lužnice river (walking distance within one hour). The agricultural systems of the settlements were probably very similar. According to our models, both settlement sites would have only needed to exploit natural resources in their immediate hinterland, within an hour walking radius. The limiting factor is the availability of suitable land for fields.According to the archaeobotanical results, the landscape in Březnice was more affected by human activity than the one in Hvožďany. A greater number of species were found, evidenced by light woodland and shrubs and different types of grassland. In the vicinity of the settlement from which people drew resources, a light landscape can be assumed. So far there is no pollen profile available. Approximately 2 m of accumulated clay and sand without organics were sampled in the floodplain of the Židova strouha. About 20 km away from Březnice, the analysis was performed in Sepekov, which base could have corresponded to the Bronze Age (2920 ± 410 BP). The character of the vegetation based on the profile could be interpreted as wet and relatively nutritious fir woodland or fir alder woodland situated on a relatively small spring area at the edge of the water meadow of the Smutná river. The palaeobotanical record in this phase does not record any effect of the settlement on the vegetation present34. The profile containing the pollen record from the Borkovická blata is located about 10 km away from Březnice. As well as the profile from Sepekov, it reflects local peat bog vegetation of the subboreal character without significant indicators of human activity107.The conditions and availability of resources in the hinterland of both settlements were probably overall so good that the details did not matter much. In the vicinity of both settlements, there were a sufficient number of areas for fields, pastures, and cultural forests. The settlement areas of the Late Bronze Age in South Bohemia were probably in separate deforested niches. More

Bacterial strains, primers, and growth conditionsBacterial strains, plasmids, and primers used in this study are shown in Supplementary Table S1. Escherichia coli strains carrying plasmids used in conjugation experiments were grown at 37 °C in LB medium. S. fredii CCBAU25509 (SF2) and its derivatives were grown at 28 °C in TY medium (5 g tryptone, 3 g yeast extract, 0.6 g CaCl2 per liter). To screen and purify conjugants or obtain pure cultures of bacteria, antibiotics were supplemented as required at the following concentrations (μg/mL): for E. coli, gentamicin (Gen), 30; and kanamycin (Km), 100; for Sinorhizobium strains, trimethoprim (Tmp), 10; nalidixic acid (Na), 30; and kanamycin (Km), 100. To screen sacB mutants from SF2 derivatives, firstly SF2 tolerance of 8%-30% sucrose in the TY medium was measured by the growth curve using Bioscreen C (Oy Growth Curves Ab Ltd, Raisio, Finland), and then the TY medium containing 10% sucrose was chosen as the selection medium.Construction of S. fredii derivatives harboring xenogeneic PsacB-sacB
The multipartite genome of SF2 consists of a chromosome (Ch, GC% = 62.6%), a chromid (pB, GC% = 62%) [31], and a symbiosis plasmid (pA, GC% = 59%) [26]. Within each replicon, an insertion position, with GC% of its 10 kb flanking region being the same as the replicon average, was chosen for subsequent experiments (Fig. 1A). The suicide plasmid pJQ200SK carries the wild-type sacB gene (characterized by its low GC content of 38.8%; 1422 bp) and its promoter region PsacB (GC% = 36.1%, 446 bp) from Bacillus subtilis subsp. subtilis str. 168 [32]. A Km-resistant cassette from pBBR1MCS-2 [33] was amplified and assembled with a linearized pJQ200SK lacking the Gm-resistant cassette using a seamless cloning kit (Taihe Biotechnology, Beijing, China) as described previously [34]. This generated pJQ-L carrying the wild-type low GC% sacB (38.8%; 1422 bp; L-GC). The sacB gene with medium (54.6%; M-GC) or high GC (61.6%; H-GC) content in its synonymous codons was synthesized (Fig. S1), and used to replace the wild-type low GC% sacB gene of pJQ-L to generate pJQ-M and pJQ-H. This was also performed using the seamless cloning method as described above with the linearized pJQ-L lacking the wild-type sacB. Three genomic segments of SF2 (pA:330682-331687, pB:702541-703493, Ch:674057-675207) were individually cloned into each of pJQ-L, pJQ-M, and pJQ-H at the SmaI site using the seamless cloning method, which allowed subsequent integration of xenogeneic cassettes into three replicons. This generated nine plasmids (pJQ-L_pA, pJQ-L_pB, pJQ-L_Ch; pJQ-M_pA, pJQ-M_pB, pJQ-M_Ch; pJQ-H_pA, pJQ-H_pB, pJQ-H_Ch), which were transformed into E. coli DH5α and verified by Sanger sequencing before conjugation into rhizobia via triparental mating with helper plasmid pRK2013 [35]. This generated nine SF2 derivatives individually carrying a xenogeneic cassette in a replicon (Fig. 1A). The correct insertion of the xenogeneic cassette was checked by PCR.Fig. 1: Screening mutations in xenogeneic sacB of different GC content.A The xenogeneic cassettes harboring sacB of L-GC, M-GC, or H-GC were individually inserted into the symbiosis plasmid (pA; GC% = 59%), chromid (pB; GC% = 62%), or chromosome (Ch; GC% = 62.6%) of Sinorhizobium fredii CCBAU25509. Gene IDs surrounding each insertion position are shown. GC% of the three sacB versions were 38.8% (L-GC, the wild-type version from Bacillus subtilis subsp. subtilis str. 168), 54.6% (M-GC, synthesized), and 61.6% (H-GC, synthesized). The wild-type PsacB (GC% = 36.1%, 446 bp) of B. subtilis 168 was cloned together with each of the three versions of sacB. The number of A, T, C, or G in the 1422 bp sacB gene is indicated. B Growth curves in TY medium. C Levansucrase enzyme activity assay of crude proteins collected at OD600 = 1.2 in TY medium. Different letters indicate significant difference (Average ± SEM; ANOVA followed by Duncan’s test, alpha = 0.05). D Growth curves in TY medium supplemented with 10% sucrose. E Schematic view of culturing, mutant screening, and mutation identification in this work. sacB, levansucrase gene; km, kanamycin resistance gene.Full size imageThe xenogeneic silencer MucR prefers low GC% DNA targets [29, 30], and its potential role in niche differentiation for IS community members was tested. SF2 has two mucR copies, and the in-frame deletion mutant ΔmucR1R2 was constructed by using an allelic exchange strategy: upstream and downstream ~500 bp flanking regions of mucR1 or mucR2 were amplified and assembled with the linearized allelic exchange vector pJQ200SK. The pJQ200SK derivative used to delete mucR1 was linearized and then cloned seamlessly with the sequence coding MucR1 and C-terminal fused FLAG-tag. The resultant plasmid was conjugated into SF2 to generate SF2MucR1FLAG. The xenogeneic cassettes carrying plasmids (pJQ-L_pA, pJQ-M_pA, pJQ-H_pA) were then inserted into the same position of pA in ΔmucR1R2 and SF2MucR1FLAG, and verified by PCR.Mutant screening and calculation of mutation frequencyTo screen sacB mutants from SF2 derivatives, single colonies of S. fredii derivatives were inoculated and grown to an OD600 = 0.2, 0.6, 1.2, and 2.0, and dilutions were applied to plates with and without 10% sucrose respectively. The number of colonies on the 10% sucrose TY plates was recorded as “A” at the dilution of 10−a, and the number of colonies on the sucrose-free TY plates was recorded as “B” at the dilution of 10−b. The total mutation frequency was then calculated by (A·10-a)/(B·10-b). Independent colonies on the 10% sucrose TY plates were further purified on the same medium plates, and the full length of PsacB-sacB fragment was amplified by colony PCR. Gene loss, SNPs or short InDels, or large insertion mutations were identified by electrophoresis analysis of PCR products. Representative clones with large insertion mutations were selected for Sanger sequencing. Three independent experiments were performed for all test strains.Enzyme activity assay for levansucraseTo evaluate the function of xenogeneic sacB in SF2 derivatives, sucrose was dissolved in the buffer solution (0.1 M CH3COONa, pH 5.5), and the total protein extract of bacteria was added (calibrated to the same concentration) to make the final concentration of sucrose 1%, and the reaction system was incubated at 28°C for 12 h. After adding the color development solution (3,5-dinitrosalicylic acid 6.3 g, sodium hydroxide 21.0 g, potassium sodium tartrate 182.0 g, phenol 5.0 g, sodium metabisulfite 5.0 g in 1000 mL water; BOXBIO, Beijing, China), the enzyme was inactivated at 95 °C for 5 min, and the absorbance value at 540 nm was measured to calculate the glucose content. Determination of the release of glucose and fructose from sucrose allowed calculation of the total activity of the levansucrase. One unit (U) of enzyme is defined as the amount of enzyme required for producing 1 µmol glucose per min in reaction buffer. The specific activity of levansucrase hydrolysis activity is the activity units per mg of protein (U/mg).5′RACETo determine the transcription start site of the sacB gene, a 5′RACE experiment was performed with the 5′RACE kit (Sangon, Beijing, China) for Rapid Amplification of cDNA Ends using three gene-specific primers (Table S1) that anneal to the known region and an adapter primer that targets the 5′ end. Products generated by 5′RACE were subcloned into the TOPO-TA vector and individual colonies were sequenced.RNA extraction and RT-qPCRTo determine transcriptional levels of the major active ISs in SF2 and its ΔmucR1R2 mutant, strains were grown in 50 mL TY liquid medium to an OD600 of 1.2. A bacterial total RNA Kit (Zomanbio, Beijing, China) was used for total RNA extraction. cDNA was synthesized using FastKing-RT SuperMix (TIANGEN, Beijing, China). qPCR was performed by using QuantStudio 6 Flex and 2× RealStar Green Mixture (Genstar, Beijing, China). The primer pairs used are listed in Table S1. The 16S rRNA gene was used as an internal reference to normalize the expression level. Three independent biological replicates were performed.ChIP-qPCRTo test the potential recruitment of MucR in the xenogeneic PsacB-sacB region, three SF2 derivative strains harboring sacB of different GC% in the pA replicon and MucR1-FLAG (Table S1; MucR1-FLAG: L-GC, MucR1-FLAG: M-GC, MucR1-FLAG: H-GC) were cultured until the OD600 had reached 1.2. Formaldehyde was added into the TY medium to a final concentration of 1%, which was then incubated at 28 °C for 15 min. To stop crosslinking, glycine was added to a final concentration of 0.1 M. The cross-linked samples were harvested (5000 × g, 5 min, 4 °C) and washed twice with cold phosphate-buffered saline (PBS). After the pellets were ground into fine powder in liquid nitrogen, the samples were resuspended in buffer containing 1% SDS and 1 mM phenylmethanesulfonyl fluoride, and lysed by sonication using a sonicator (Q800R3, QSonica). Chromatin immunoprecipitation (ChIP) was performed using the ChIP assay kit (Beyotime, Shanghai, China) according to the manufacturer’s recommendations. The supernatant was collected and chromatin was immunoprecipitated with Anti-FLAG M2 antibody (Sigma). Input control and DNA obtained from the immunoprecipitation were amplified by PCR using primers listed in Table S1. The recruitment level of FLAG-tagged MucR1 in multiple regions within the PsacB-sacB fragment inserted by ISs at high frequency was detected by ChIP-qPCR.Crosslinking and western blotting assayTo test the ability of MucR1 to form homodimer in SF2 derivatives carrying sacB in pA, rhizobial cells (SF2MucR1FLAG, MucR1-FLAG: L-GC, MucR1-FLAG: M-GC, and MucR1-FLAG: H-GC) were cultured in 50 mL TY medium to an OD600 of 1.2. Formaldehyde was added at a final concentration of 1% in the culture which was then shaken at 28 °C, 100 rpm for 15 min to allow crosslinking. The crosslinking reaction was terminated by adding a final concentration of 100 mM glycine (28 °C, 100 rpm, 5 min). 1 mL of the above solution was centrifuged (5000 × g, 4 °C, 1 min), resuspended in 50 µL SDS loading buffer to a uniform cell density, and then boiled for 10 minutes for lysis. Next, lysates were separated on 12% SDS-PAGE and transferred to a nitrocellulose membrane. For immunodetection of individual proteins, the method described previously was used [30]. Briefly, mouse monoclonal Anti-FLAG M2 antibody (Sigma), HRP (horseradish peroxidase) conjugated goat Anti-mouse IgG (Abcam), and eECL Western blot kit (CWBIO, Beijing, China) were used, and chemiluminescence signals were visualized using Fusion FX6 (Vilber) and Evolution-Capt Edge software.Protein purificationTo purify MucR1 protein, E. coli BL21(DE3) carrying His6-SUMO-tagged MucR1 in the pET30a [29] was cultured in 500 mL LB medium until OD600 reached 0.8. The procedure described previously was used [30]. IPTG was then added to the culture to a final concentration of 0.6 mM and switched to 18 °C at 150 rpm for 12 h. Cells were harvested by centrifugation (5000 × g, 5 min, 4 °C) and resuspended in 30 mL of lysis buffer (25 mM Tris, pH 8.0, 250 mM NaCl, 10 mM imidazole) supplemented with 0.1 mg/mL DNase I, 0.4 mg/mL of lysozyme, and protease inhibitor mixture (Roche). After 30 min incubation and 120 sonication cycles (300 W, 10 s on, 10 s off), lysates were removed by centrifugation (18,000 × g, 4 °C, 30 min) and filtration through a 0.22 μm membrane. The supernatant was loaded onto Ni-Agarose Resin (CWBIO, Beijing, China) pre-washed using lysis buffer, washed 3 times with wash buffer (lysis buffer containing 20 mM imidazole), and then eluted by lysis buffer containing imidazole gradient (100, 200, 300 mM imidazole). The purified proteins were finally concentrated by ultrafiltration and redissolved in storage buffer (25 mM Tris, pH 8.0, 250 mM NaCl, 10% glycerol) prior to use or storage at −80 °C.DNA bridging assayTo determine if MucR1 can form DNA-MucR1-DNA complex with various regions of xenogeneic PsacB-sacB fragment, a DNA bridging assay described earlier [30, 36] was performed with modifications. DNA probes were prepared by annealing of synthesized complementary strands (PsacB −90~−24) or by PCR amplification (PsacB −90~+3, sacB +710~+802, sacB +908~+1007) using 5′-biotin-labeled or 5′-Cy5 primers (Table S1). In each bridging assay, 100 μL of hydrophilic streptavidin magnetic beads (NEB) were washed twice with 500 μL of PBS and then resuspended in 500 μL of coupling buffer (20 mM Tris-HCl, pH 7.4, 1 mM EDTA, 500 mM NaCl). Then, the suspension was supplied with 10 pmol of biotin-labeled DNA and incubated with the beads for 30 min at room temperature with gentle rotation. The resulting beads were washed twice with 500 μL of incubation buffer (20 mM Tris, pH 7.4, 150 mM NaCl, 1 mM dithiothreitol, 5% glycerol (vol/vol), 0.05% Tween 20) and resuspended after the addition of 10 pmol Cy5-labeled DNA and 10 μL HRV 3C protease to a final volume of 500 μL. The HRV 3C protease was used herein to remove SUMO. A twofold serial dilution of the protein sample was added to each 50 μL aliquot of bead suspension, and supplemented with incubation buffer to 60 μL final volume. After 30 minutes of incubation with gentle rotation at room temperature, the mixture was placed on a magnetic stand for 5 minutes. The supernatant was collected and labeled as Sample A. The beads were mixed with 60 μL of elution buffer (incubation buffer with 0.1% SDS and 20 μg/mL biotin) and incubated in a boiling water bath for 10 min. The eluted samples were labeled as Sample B. Cy5 fluorescence signals of Sample A and B were detected by a Microscale Thermophoresis Monolith NT.115 system (NanoTemper). The Cy5 fluorescence signal of the Sample A from the treatment without MucR1 was defined as 100% input signal.Statistical analysesAnalysis of variance (ANOVA) followed by Duncan’s test, Student’s t-test, and Fisher’s exact test were performed using GraphPad Prism 8. The closest homolog of individual active ISs and their family identification were determined using ISfinder [37]. Target sequence logos of ISs were generated by multiple sequence alignments of insertion sites within xenogeneic PsacB-sacB or genomic background using the program WebLogo [38].Although the fundamental niche, not constrained by biological interactions, cannot be determined by observation [15], the realized niche, representing a proportion of the fundamental niche where organisms actually live under abiotic and biotic interactions, can be estimated by correlative approaches [15, 39]. In order to address the influence of intracellular variables on biased IS insertions into nine common gardens, the within outlying mean index analysis developed for niche differentiation analysis was carried out using the R package “subniche” [40, 41]. The intracellular environmental gradients were determined by Principal Component Analysis (PCA) based on variables as follows: GC% of different sacB versions, replicon GC%, the number of each IS in the corresponding replicon where sacB is inserted, available insertion sites of ISs in different sacB versions, and levansucrase activity of strains carrying different sacB versions. Within this multidimensional Euclidean space (environmental space), mean positions in realized (sub)niches and parameters of each IS were obtained for the whole data set (realized niches in environmental space defined by nine common gardens) or various subsets (realized subniches in sub-environmental spaces identified by the hierarchical clustering analysis with the ward.D method based on the Euclidean distance matrix) [41]. Two and three subsets rather than four and more subsets were statistically analyzable. By comparing to the overall average habitat conditions (G) or the average subset habitat conditions (GK) of the spatial domain, ISs selecting for a less common habitat were indicated by their significantly higher niche marginality values compared to the simulated values, based on a Monte Carlo test with 1,000 permutations, under the hypothesis that each IS is indifferent to its intracellular environment [40]. More

Annual grains, domesticated from wild species, have dominated agriculture since the Neolithic. A new study reports how turning to high-yield perennial rice crops could maintain key ecosystem functions while supporting livelihoods.The past several decades have seen modest but growing investments in the development of perennial grain crops, including perennial counterparts of wheat, rice and sorghum suitable for the USA, China, Europe and Africa. One technique involves domesticating wild perennial species through continual selection of desirable traits over multiple generations3. A recently developed perennial grain currently grown for niche markets in the USA, Kernza, was domesticated from Thinopyrum intermedium, a wild relative of wheat. While yields of Kernza remain low compared with those of annual wheat, they are increasing. As with the development of perennial rice, plant breeders can also cross perennial species with domesticated annual relatives to produce perennial hybrids with desirable traits derived from the annual parent3. More

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doi: https://doi.org/10.1038/d41586-022-03776-4

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Conservation biology More

Data acquisition and preparationStructured datasetsWe used structured North American Breeding Bird Survey (BBS) data, which is conducted annually over  > 2500 routes across the United States and Canada11,12 during the peak of the breeding season (May and June). BBS routes were approximately 40 km long with 50 stops spaced 0.8 km apart. At each stop a 3-min point count was conducted, where all species seen or heard were recorded12. We downloaded the entire dataset, 1966–2019, to identify each observer’s first year and account for differences in survey experience. We created a binary variable for the observers’ first year, with 1 indicating the first year they provided data, and 0 indicating all subsequent years. We then subset the data to years 2010–2019 to align with available community science data. We zero-filled BBS data by adding zeros for each species on routes in which birds were not detected in each year.Semi-structured datasetWe used the eBird Basic Dataset as a semi-structured dataset. We used checklists within the US and Canada during June and July from 2010 to 2019. Data were filtered to impose structure on the observation process and minimize effects of unequal spatial and temporal sampling using the auk package in program R24,25,56,59,60. Data were filtered to only include complete checklists where observers recorded counts of all species detected to reduce effects of preferential species reporting61. We also filtered data based on observer effort to only include checklists  More

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