Philippa Kaur

The copy numbers for 16S and ITS1 rRNA, and the sequencing depth for all samples are presented in Supplementary File 3 (qPCR data, Sequencing Rarefaction Curves). An average of 14,265.25 reads per housefly sample for the V4 16SrRNA and 16,149.4 reads per housefly sample for the ITS1 were retained after quality filtering. After quality filtering of the egg-laying substrate samples, an average of 10,371.75 reads were retained per sample for the V4 16SrRNA, and an average of 25,479.75 reads were retained per sample for the ITS1 region. The extracted DNA from newly emerged adult houseflies of the Spanish laboratory strain (12 samples in total, newly emerged adults, three replicates from four generations, strain SP100) returned a low copy number for the fungal ITS1 (qPCR data, Supplementary File 3) and a low number of acquired sequencing reads; they were therefore omitted from any further analysis of the fungal microbiota. In addition, the mitochondrial COI phylogeny showed that the Dutch wild-caught strain and the Dutch laboratory strain, which were sampled from the same locality at different times, are in close proximity and form a separate clade from the Spanish lab strain phylotypes (Supplementary File 2).The housefly microbiota alpha-diversity is determined by sampling environmentAbsolute richness (number of ASVs), Shannon index, and Phylogenetic diversity for all housefly strains and developmental stages are shown in Fig. 1. The highest bacterial alpha diversity was observed for the wild-caught housefly population GK0. Strain was an important factor for separating Shannon biodiversity levels both for newly emerged (F = 4.37, P  More

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Prosopis juliflora leaves collection and processing for RibotypingProsopis juliflora species of the genus Prosopis, family of Fabaceae had its genetic variation in Doha evaluated. Seven samples of P. juliflora leaves were collected from six different locations in Doha, Qatar, during five field trips. Plant leaves were collected after proper permissions and all methods were carried out in accordance with relevant guidelines and regulations. Trees in all locations were naturally growing around urbanization areas in their normal arid habitat without artificial irrigation, samples were collected from fully mature trees. Table 1 shows the samples details. Figure 1 shows the location sites of where the samples were collected on the map of Qatar, Doha. Leaf samples were kept in sterile labeled bags until having reached the laboratory where few leaflets were washed with sterile distilled water and sterilized using 70% ethanol to be used for DNA extraction.Table 1 Location details of the collection sites of P. juliflora leaves.Full size tableFigure 1Location map of collection sites of P. juliflora leaf samples (ArcGIS software).Full size imageRibotyping analysisThe leaflets of each sample were transferred into a sterile mortar previously cooled at -20 ˚C and used for DNA extraction following the kit manufacturer instructions (DNeasy Plant Mini Kit-QIAGEN-USA).Extracted DNA of each sample were subject to PCR using ITS1 and ITS4 primers. PCR products obtained were purified using the Invitrogen Quick PCR Purification Kit (QIAGEN, Germany) as indicated by the manufacturer and sequenced using Sanger sequencer (3130/3130xl DNA Analyzers, Thermofisher Scientific, USA) as previously described22.Sanger sequencer raw data was read using BioEdit software. Basic Local Alignment Search Tool (BLAST) network services of the National Centre for Biotechnology Information (NCBI) database were used to compare the obtained sequences to the existing sequences. Sequences were submitted to NCBI for accession numbers. The various P. juliflora ribosomal sequences obtained were also uploaded on MEGA-X software and the phylogeny tree was generated using the neighbor-joining algorithm26.Minimum inhibitory concentrations of PJ-WS-LE extracts prepared using leaf samples collected from various locations against A. alternata and C. gloeosporioides
Preparation of PJ-WS-LE extractFresh, young full leaves of P. juliflora were collected from various locations as indicated in Fig. 1. Samples were washed, dried and ground into powder to be used in the preparation of PJ-WS-LE extract as previously described22. Briefly, every 20 g of the leaf powder were incubated in 200 mL of 70% ethanol for 48 h. The supernatant has its solvent evaporated, the extract was then re-dissolved in sterile distilled water. Only water-soluble phytochemicals were tested by centrifuging the final preparation tubes and excluding the pellet. Stock solution of 100 g L−1 was stored at 4 °C to be used for later experiments. PJ-WS-LE extract concentration used in treatments was 8 g L−1 which is double the highest minimum inhibitory concentration of the extract against spoiling microorganisms as previously determined22.Determination of minimum inhibitory concentrationThe MIC test was conducted in a sterile 96-well plate, with each well containing 100 μl of potato dextrose broth (PDB) (HIMEDIA-India). Every four wells made one replication, nine different concentrations of the crude extracts were tested (1:1 dilutions) ranging from 42 to 0.16 g L−1. Wells were then inoculated with one of the two tested microorganisms’ spore suspensions (A. alternata and C. gloeosporioides). The last three rows are control rows: no spores and no extract control wells, negative control with spores but no extract wells, and positive control with spores and 10 µl of the fungicidal Clatrimazole (1%) wells.Fungal spore suspensions were adjusted to the range of 104 spores L−1 using a 10 day old fungal plate and sterile distilled water, the spore concentration was calculated using a heamatocytometer.Fungal growth in each well was monitored using Resazurin (HIMEDIA-India) dye. Upon cells division, Resazurin changes its color from blue to pink and fluorescent27. Results were taken within 48 h of incubation at 25 °C. MIC was recorded as the last extract concentration that shows no change in the color of Resazurin within the incubation period.Curative and preventive effects of PJ-WS-LE extract against A. alternata and C. gloeosporioides induced infection in mangoesPathogensThe two fungal strains used C. gloeosporioides and A. alternata were obtained from our laboratory collection, Department of Biological and Environmental Sciences, Qatar University, Qatar. Both fungal isolates were previously isolated from locally collected fruit samples. Isolates were molecularly identified by sequencing the Internal Transcribed Spacer (ITS) regions of fungal ribosomal DNA (rDNA) that was amplified by PCR. Identified fungal isolates were given the strains code of AaltQU17 for A. alternata and CgloQU17 for C. gloeosporioides22. Preserved cultures were sub-cultured on potato dextrose agar (PDA) plates and incubated at 25 °C for 10 days. Plates were then flooded with 10 mL of sterile distilled water each, to prepare the needed spores suspension solutions. The concentrations of spores suspensions were adjusted to 106 spores L−1 using a heamatocytometer18.FruitThe mango (Mangifera indica) type known as Neelam imported from India was used in the experiments. Fruit were bought from the whole sale market upon their arrival to the country. Only undamaged mature fruit were used in the experiment. Fruits chosen were ripen but not yet soft with firmness average of 20 ± 5.1 N, weight average of 177.61 ± 0.2 g and TSS average of 70 ± 5.3%. Fruit were first washed with sink water and sterilized twice with 70% ethanol to be then washed with sterile distilled water and left to air dry.Preventive and curative effects of PJ-WS-LE extractWounded mango fruit were used during the experiment, the wounds were made through three needle pricks (2 mm deep) in three different places for each plant using a sterile syringe. A completely randomized design was used and each treatment was made of a triplicate of 10 fruit each. The experiment was repeated twice.PJ-WS-LE extract of leaves collected from Qatar university field was first tested for its efficacy in preventing fungal contamination in wounded mango fruit (preventive effect). Therefore, the wounded zone of each fruit was sprayed with 8 g L−1 PJ-WS-LE extract and then left to air-dry. Once dry the fruit were sprayed again with the extract at the same concentration and left to dry. Control fruit were only treated with sterile distilled water without the plants extract. After two hours all wounds were inoculated with 20 μL of conidia aqueous solution (106 spores mL−1) of one of the tested fungi. The extract was then tested for its ability to cure fungal contamination in wounded fruit. Therefore, wounds were inoculated first with 20 μL of conidia aqueous solution (106 spores mL−1) and left to dry. Wounds were then sprayed twice with 8 g L−1 PJ-WS-LE extract.All mangoes were stored in sterilized plastic trays inside an incubator at 25 °C and 75% humidity. Fruit were observed every 24 h for 5 days for C. gloeosporioides inoculated fruit and for 10 days for A. alternata inoculated fruit. Three parameters were recorded at the end of the experiment: disease incidence (DI), disease severity (DS), and percent plant extract efficacy (%EE). To calculate disease severity, the diameter of the infected area of each fruit was measured in two perpendicular directions and mean diameter mycelial growth was calculated28,29.$$mathrm{DI}=frac{(mathrm{Number, of, rotten, fruit})times 100}{mathrm{Total, number, of, fruit}}$$$$mathrm{DS }=frac{(mathrm{Average, lesion, diameter, of, treated, plants})times 100}{mathrm{Average, Lesion, diameter, of, control, plants})}$$$$mathrm{%EE}=frac{(mathrm{Disease, incidence, in, Control, batch}-mathrm{Disease, incidence, in, treated, batch})times 100}{mathrm{Disease, incidence, in, Control, batch}}$$End of the trial samples firmnessAt the end of the trial, remaining mango fruit were tested for their flesh quality using a penetrometer (Agriculture Solutions, USA) to test the flesh firmness. Fruit were peeled, then the stainless steel probe of the instrument was inserted in three different points towards the equator of the fruit. Firmness in Newton was recorded and compared with standard fruit firmness to judge fruit quality18.Effectiveness of PJ-WS-LE extract as long-term coating material and the preservative value of its chitosan-embedded formCoating solutions preparationChitosan solution of 1% concentration was prepared by stirring chitosan powder (CAS 9012-76-4, Himedia, India) in 1% glacial acetic acid (IsoLab, Germany) overnight. The final chitosan solution pH was adjusted to 5.6 using 0.1 M NAOH (Sigma-Aldrich, Germany). To prepare PJ-WS-LE extract chitosan-embedded coating material, filter-sterilized PJ-WS-LE extract stock solution was added to 1% chitosan to achieve a final concentration of 8 g L−130.Samples preparationEighty-four mango samples chosen as described above, were divided into four groups of 18 samples each. Samples were divided into four treatment batches and treated as following:

Batch A: non-treated fruit.

Batch B: PJ-WS-LE extract at 8 g L–1 was used to spray the fruit.

Batch C: 1% chitosan was used to spray the fruit.

Batch D: 8 g L−1 PJ-WS-LE extract embedded in 1% chitosan was used to spray the fruit.

Every experimental replicate was made up of three mango samples that were stored together in one sterile bag at 4 °C. The number of replications per treatment was six. The experiment was repeated twice31.Evaluation of sensory qualityA five-points scale was used for the evaluation of the sensory quality of the samples for overall quality, smell, and color change. The attributes were evaluated weekly using the fruit of one experimental replicate. Scores were given using the following scale: 5 points indicate “extremely liked”, 4 points indicate “liked”, 3 points indicate “acceptable” 2 points indicate “disliked” and 1 point indicates “extremely disliked”. The weekly average score per batch was also calculated32.Estimation of weight lossUpon treatment at day zero, all mango samples were weighed and their weights were recorded as initial weights. Weights of all remaining samples were measured at the end of every week. The variation between the start weight and weekly weights is calculated as weekly weight loss. The average percent of weekly weight loss of each batch was calculated32.Determination of samples firmnessThe samples of each experimental replicate evaluated on a weekly basis had their firmness measured as previously described. The weekly average samples firmness (N) of every treatment batch was also calculated33.pH measurementMango fruit of each experimental replicate were blended weekly into juice, after filtration, a digital pH meter (Jenway, UK) was used to measure pH. The weekly average fruit pH of every treatment batch was also calculated. The pH meter was calibrated using a buffer solution of pH 734.Total soluble solids (TSS) measurementTotal soluble solids of the prepared mango juice samples were measured in percent brix using a refractometer (ANTAHI, New Zealand). The weekly average fruit TSS (%) for each treatment batch was also calculated. The refractometers was calibrated using distilled water35.DPPH radical scavenging assayA 1/10 mango juice dilution was prepared using sterile distilled water. 100 μL of each dilution was mixed with 1 mL of 2,2-diphenyl-1-picrylhydrazyl (DPPH) (100 mg L−1) to be incubated in the dark at 37 °C for 45 min. After incubation, samples were centrifuged and the pellet was discarded. The intensity of the change in color of the supernatant was measured by spectrophotometry at 517 nm using methanol as a blank. 100 μL of methanol in 1 mL DPPH was used as the control for the experiment. Percent radical scavenging activity was calculated as per the below formula:$$ % {text{ radical scavenging activity}}, = ,left( {{text{absorbance of the control solution}} – {text{ absorbance of the juice sample}}} right)*{1}00/{text{absorbance of the control solution}}. $$The weekly average % radical scavenging activity for each treatment batch was finally calculated31.Statistical analysisThe experimental design used was Completely Randomized Design (CRD). One-way ANOVA followed by Tukey Post-Hoc test was used to evaluate the significance of the weekly percent change in weight among treatment batches at P ≤ 0.05. The significances of pH and TSS variation within different treatment batches were evaluated using One-way ANOVA test at P ≤ 0.05. Data was presented as average ± standard error of the Means (SEM). SPSS (Ver. 27, SPSS Inc. Chicago, USA) was used to perform the statistical analysis tests. More

Dynamic in-flight flock organizationIt is commonly assumed that during flocking, flock members follow three basic interaction rules: Attraction, Repulsion and Alignment, to coordinate spatial positions between each other18. To study the spatial organization of our zebra finch flock during flight, the spatial positions of all birds in the flight section were tracked in every fifth frame (sample rate: 24 Hz (that is, frames per second)) of the synchronized footage recorded by two high-speed digital video cameras (Camera 1: centred upwind view, Fig. 1a,b; Camera 2: upturned vertical view, Fig. 1a,c) for the entire duration (51.7, 58.3, 69.2 and 127 s) of four (session 2, 5, 8 and 13) out of 13 flight sessions. Flight paths were reconstructed from the tracking data for each bird in the flock, with horizontal and vertical coordinates delivered by Camera 1 and coordinates in wind direction delivered by Camera 2. The data show that each bird mainly occupied a particular area in the flight section, and that this spatial preference was stable over different flight sessions. Bird Green, for example, was preferentially flying very low above the flight section’s floor, and bird Lilac preferred to fly at upwind positions in front of the flock (Fig. 1d, Extended Data Figs. 1 and 3 and Supplementary Information).Despite their preference in flight area, all birds constantly changed their spatial positions fast and rhythmically along the horizontal dimension of the flight section (Fig. 1e–g, Extended Data Figs. 2 and 4, Supplementary Video 1 and Supplementary Information). This behaviour is reminiscent of the flight behaviour of wild zebra finches: when being surprised in flight by a predator, zebra finches fly in a rapid zig-zag course low above the ground, heading for nearby vegetation16. Whether the sideways oscillating flight manoeuvres, which are performed by both wild birds in open space and domesticated birds in the wind tunnel’s flight section, are caused by the close proximity to the ground or are part of an escape reaction is yet unknown.From the tracking data, we further calculated the spatial distances in all three dimensions between all pairwise combinations of birds throughout the four flight sessions (sample rate: 24 Hz). When normalized to the maximum distance detected for each bird pairing, each dimension and each flight session, mean distances of bird pairings in all dimensions were narrowly distributed within a range of 27.7–38.0% of maximum distance (Fig. 1h and Supplementary Table 1). This may indicate that during flocking flight, zebra finches actively balance Attraction and Repulsion to maintain a stable 3D distance towards all other members of the flock. Owing to the spatial limitations in the wind tunnel’s flight section, we did not expect the zebra finches to perform large-scale flight manoeuvres with movements aligned between all flock members (Extended Data Fig. 5 and Supplementary Information), as can be observed, for example, in freely flying flocks of homing pigeons (Columba livia domestica)19 and white storks (Ciconia Ciconia)20.Visually guided horizontal repositioningWhen observing the dynamic spatial organization of our zebra finch flock, a question immediately arises: how do the birds prevent collisions during their frequent horizontal position changes? When considering the spatial limitation experienced by the flock of six birds during flight in the flight section and their highly dynamic flight style, collision rates seemed to be astonishingly low (median: 0.02 Hz; interquartile range (IQR): 0–0.03 Hz; n = 13 sessions) during flocking flight (in total 16 collisions in 13 min of analysed flight time). In birds, the visual system represents the main input channel for environmental information. To tackle the above question, we therefore first investigated the role of vision during flocking flight, and tested whether a bird’s viewing direction was correlated with the direction of horizontal position change. As gaze changes are governed by head movements in birds21, we used a bird’s head direction as an indicator for the orientation of its visual axis. We tracked (sample rate: 120 Hz) the position of a bird’s beak tip and neck in each frame of the footage during ten horizontal position changes (Fig. 2a and Supplementary Video 2) per bird, and found a strong interaction between a bird’s head angle relative to the wind direction and its direction of horizontal position change. During horizontal position changes, the birds always turned their heads in the direction of the position change (Fig. 2b). While the population’s median absolute angle of position change was 84.0° (IQR: 78.6–87.2°; n = 60) relative to 0° in wind direction, the population’s median absolute head turning angle was 36.0° (IQR: 26.4–42.5°; n = 60; see Supplementary Information for results on head movements during solo flight). The eyes of zebra finches are positioned laterally on their heads22 and each retina features a small region of highest ganglion cell density (fovea, that is, region of highest visual spatial resolution) at an area that receives visual input from horizontal positions at 60° relative to the midsagittal plane23. By turning their heads by about 36° during horizontal position changes, the zebra finches roughly align the foveal area in the retina of one eye with their direction of position change, and in the retina of the other eye with the wind direction (Fig. 2c,d). Thus, head turns in the direction of position change may indicate that the birds use visual cues while repositioning themselves within the flock. This hypothesis is supported by a study on zebra finch head movements performed during an obstacle avoidance task. In this study, instead of fixating on the obstacle, zebra finches turned their head in the direction of movement while navigating around the obstacle24.Fig. 2: Horizontal position changes are accompanied by head turns.a, Head and body orientation of bird Orange (ventral view) during one example of position changes to the right, tracked (sample rate: 120 Hz) in the footage of Camera 2. Circles: beak tip positions; plus signs: neck positions; upward pointing triangles: tail base positions. Cutouts of freeze frames of the footage taken with Camera 2 show the bird’s head and body posture for 11 time points during the position change. b, In all birds, the median angle of head turn during horizontal position change in flocking flight is positively correlated (linear mixed effects model (LMM), estimates ± s.e.m.: 2.05 ± 0.1, P  More