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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Tracking ebolavirus genomic drift with a resequencing microarray

Filoviruses are emerging pathogens that cause acute fever with high fatality rate and present a global public health threat. During the 2013–2016 Ebola virus outbreak, genome sequencing allowed the study of virus evolution, mutations affecting pathogenicity and infectivity, and tracing the viral spread. In 2018, early sequence identification of the Ebolavirus as EBOV in the Democratic Republic of the Congo supported the use of an Ebola virus vaccine. However, field-deployable sequencing methods are needed to enable a rapid public health response. Resequencing microarrays (RMA) are a targeted method to obtain genomic sequence on clinical specimens rapidly, and sensitively, overcoming the need for extensive bioinformatic analysis. This study presents the design and initial evaluation of an ebolavirus resequencing microarray (Ebolavirus-RMA) system for sequencing the major genomic regions of four Ebolaviruses that cause disease in humans. The design of the Ebolavirus-RMA system is described and evaluated by sequencing repository samples of three Ebolaviruses and two EBOV variants. The ability of the system to identify genetic drift in a replicating virus was achieved by sequencing the ebolavirus glycoprotein gene in a recombinant virus cultured under pressure from a neutralizing antibody. Comparison of the Ebolavirus-RMA results to the Genbank database sequence file with the accession number given for the source RNA and Ebolavirus-RMA results compared to Next Generation Sequence results of the same RNA samples showed up to 99% agreement.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

A global soil plasmidome resource unveils functional and ecological roles of plasmids in soil microbiomes

Plasmids play significant roles in microbial adaptation to ecosystems, yet their dynamics remain poorly understood due to identification challenges. We present the Global Soil Plasmidome Resource (GSPR), a comprehensive dataset of 98,728 plasmid sequences amassed from 6860 terrestrial microbial communities and isolates. We explore this resource through various computational approaches, including phylogenetic diversity analysis, host prediction, and extensive functional annotation, to understand the contribution of plasmids to the genetic and functional diversity in soil, correlating these findings with sample type, as well as the soil habitat they were retrieved from. Our analysis reveals insights into plasmid-encoded functions such as effector modules, quorum sensing, and stress resistance, which may contribute to their persistence and microbial adaptation in soil. Furthermore, CRISPR analysis suggests a prevalent role of these elements related to intra-plasmid competition. By contrasting plasmids from cultivated and uncultivated organisms, we identify important functions that expand existing knowledge of plasmid roles in these habitats. This study represents a notable step forward in elucidating plasmid diversity and function within soil microbiomes and establishes a foundational framework for exploring their roles in natural environments.

Fiamenghi, Mateus B↗
DOE OSTI2022

Characterization of a novel HIV-1 circulating recombinant form, CRF91_cpx, comprising CRF02_AG, G, J, and U, mostly among men who have sex with men

Prospective molecular studies of HIV-1 pol region (2253–5250 in HXB2 genome) sequences from sequenced samples of 269 HIV-1-infected patients in Cyprus (2017–2021) revealed a transmission cluster of 14 unknown HIV-1 recombinants that were not classified as previously established CRFs. The earliest recombinant was collected in September 2017, and the transmission cluster continued to grow until November 2020. Near full-length HIV-1 genome sequences of the 11 of the 14 recombinants were successfully obtained (790–8795 in HXB2 genome) and aligned against a reference dataset of HIV-1 subtypes and CRFs. We employed MEGAX for maximum-likelihood tree construction (GTR model, 1000 bootstrap replicates), Cluster-Picker for phylogenetic clustering analysis (genetic distance ≤0.045, bootstrap support value ≥70%), and REGA-3.0 for subtype determination. Bootscan and similarity plot analyses (sliding window of 400 nucleotides overlapped by 40 nucleotides) were conducted using SimPlot-v3.5.1, and subregion confirmatory neighbour-joining tree analyses were conducted using MEGAX (Kimura two-parameter model, 1000 bootstrap replicates, ≥70% bootstrap-support value). Exclusive clustering of the HIV-1 recombinants revealed their uniqueness. The recombination analyses illustrated the same unique mosaic pattern with six putative intersubtype recombination breakpoints, seven fragments of subtypes CRF02_AG, G, J and an unclassified fragment. We conclusively characterized the mosaic structure of the novel HIV-1 CRF, named CRF91_cpx, by the Los Alamos HIV Sequence Database. Additionally, we identified a URF of CRF91_cpx with two additional recombination sites, generated by a recombination event between subtype B and CRF91_cpx. Since the identification of CRF91_cpx, two additional patient samples have been entered into the CRF91_cpx transmission cluster, demonstrating active growth.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Deep Learning and Likelihood Approaches for Viral Phylogeography Converge on the Same Answers Whether the Inference Model Is Right or Wrong

Abstract Analysis of phylogenetic trees has become an essential tool in epidemiology. Likelihood-based methods fit models to phylogenies to draw inferences about the phylodynamics and history of viral transmission. However, these methods are often computationally expensive, which limits the complexity and realism of phylodynamic models and makes them ill-suited for informing policy decisions in real-time during rapidly developing outbreaks. Likelihood-free methods using deep learning are pushing the boundaries of inference beyond these constraints. In this paper, we extend, compare, and contrast a recently developed deep learning method for likelihood-free inference from trees. We trained multiple deep neural networks using phylogenies from simulated outbreaks that spread among 5 locations and found they achieve close to the same levels of accuracy as Bayesian inference under the true simulation model. We compared robustness to model misspecification of a trained neural network to that of a Bayesian method. We found that both models had comparable performance, converging on similar biases. We also implemented a method of uncertainty quantification called conformalized quantile regression that we demonstrate has similar patterns of sensitivity to model misspecification as Bayesian highest posterior density (HPD) and greatly overlap with HPDs, but have lower precision (more conservative). Finally, we trained and tested a neural network against phylogeographic data from a recent study of the SARS-Cov-2 pandemic in Europe and obtained similar estimates of region-specific epidemiological parameters and the location of the common ancestor in Europe. Along with being as accurate and robust as likelihood-based methods, our trained neural networks are on average over 3 orders of magnitude faster after training. Our results support the notion that neural networks can be trained with simulated data to accurately mimic the good and bad statistical properties of the likelihood functions of generative phylogenetic models.

Evolutionary Biology↗
DOE OSTI2023

Evolutionary lineage explains trait variation among 75 coexisting grass species

Summary Evolutionary history plays a key role driving patterns of trait variation across plant species. For scaling and modeling purposes, grass species are typically organized into C 3 vs C 4 plant functional types (PFTs). Plant functional type groupings may obscure important functional differences among species. Rather, grouping grasses by evolutionary lineage may better represent grass functional diversity. We measured 11 structural and physiological traits in situ from 75 grass species within the North American tallgrass prairie. We tested whether traits differed significantly among photosynthetic pathways or lineages (tribe) in annual and perennial grass species. Critically, we found evidence that grass traits varied among lineages, including independent origins of C 4 photosynthesis. Using a rigorous model selection approach, tribe was included in the top models for five of nine traits for perennial species. Tribes were separable in a multivariate and phylogenetically controlled analysis of traits, owing to coordination of important structural and ecophysiological characteristics. Our findings suggest grouping grass species by photosynthetic pathway overlooks variation in several functional traits, particularly for C 4 species. These results indicate that further assessment of lineage‐based differences at other sites and across other grass species distributions may improve representation of C 4 species in trait comparison analyses and modeling investigations.

Donnelly, Ryan C.↗
DOE OSTI2022

A deep learning approach to real-time HIV outbreak detection using genetic data

Pathogen genomic sequence data are increasingly made available for epidemiological monitoring. A main interest is to identify and assess the potential of infectious disease outbreaks. While popular methods to analyze sequence data often involve phylogenetic tree inference, they are vulnerable to errors from recombination and impose a high computational cost, making it difficult to obtain real-time results when the number of sequences is in or above the thousands. Here, we propose an alternative strategy to outbreak detection using genomic data based on deep learning methods developed for image classification. The key idea is to use a pairwise genetic distance matrix calculated from viral sequences as an image, and develop convolutional neutral network (CNN) models to classify areas of the images that show signatures of active outbreak, leading to identification of subsets of sequences taken from an active outbreak. We showed that our method is efficient in finding HIV-1 outbreaks with R0 ≥ 2.5, and overall a specificity exceeding 98% and sensitivity better than 92%. We validated our approach using data from HIV-1 CRF01 in Europe, containing both endemic sequences and a well-known dual outbreak in intravenous drug users. Our model accurately identified known outbreak sequences in the background of slower spreading HIV. Importantly, we detected both outbreaks early on, before they were over, implying that had this method been applied in real-time as data became available, one would have been able to intervene and possibly prevent the extent of these outbreaks. This approach is scalable to processing hundreds of thousands of sequences, making it useful for current and future real-time epidemiological investigations, including public health monitoring using large databases and especially for rapid outbreak identification.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

A natural mutation between SARS-CoV-2 and SARS-CoV determines neutralization by a cross-reactive antibody

Epitopes that are conserved among SARS-like coronaviruses are attractive targets for design of cross-reactive vaccines and therapeutics. CR3022 is a SARS-CoV neutralizing antibody to a highly conserved epitope on the receptor binding domain (RBD) on the spike protein that is able to cross-react with SARS-CoV-2, but with lower affinity. Using x-ray crystallography, mutagenesis, and binding experiments, we illustrate that of four amino acid differences in the CR3022 epitope between SARS-CoV-2 and SARS-CoV, a single mutation P384A fully determines the affinity difference. CR3022 does not neutralize SARS-CoV-2, but the increased affinity to SARS-CoV-2 P384A mutant now enables neutralization with a similar potency to SARS-CoV. We further investigated CR3022 interaction with the SARS-CoV spike protein by negative-stain EM and cryo-EM. Three CR3022 Fabs bind per trimer with the RBD observed in different up-conformations due to considerable flexibility of the RBD. In one of these conformations, quaternary interactions are made by CR3022 to the N-terminal domain (NTD) of an adjacent subunit. Overall, this study provides insights into antigenic variation and potential cross-neutralizing epitopes on SARS-like viruses.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Neutralization profiles of HIV-1 viruses from the VRC01 Antibody Mediated Prevention (AMP) trials

The VRC01 Antibody Mediated Prevention (AMP) efficacy trials conducted between 2016 and 2020 showed for the first time that passively administered broadly neutralizing antibodies (bnAbs) could prevent HIV-1 acquisition against bnAb-sensitive viruses. HIV-1 viruses isolated from AMP participants who acquired infection during the study in the sub-Saharan African (HVTN 703/HPTN 081) and the Americas/European (HVTN 704/HPTN 085) trials represent a panel of currently circulating strains of HIV-1 and offer a unique opportunity to investigate the sensitivity of the virus to broadly neutralizing antibodies (bnAbs) being considered for clinical development. Pseudoviruses were constructed using envelope sequences from 218 individuals. The majority of viruses identified were clade B and C; with clades A, D, F and G and recombinants AC and BF detected at lower frequencies. We tested eight bnAbs in clinical development (VRC01, VRC07-523LS, 3BNC117, CAP256.25, PGDM1400, PGT121, 10–1074 and 10E8v4) for neutralization against all AMP placebo viruses (n = 76). Compared to older clade C viruses (1998–2010), the HVTN703/HPTN081 clade C viruses showed increased resistance to VRC07-523LS and CAP256.25. At a concentration of 1μg/ml (IC80), predictive modeling identified the triple combination of V3/V2-glycan/CD4bs-targeting bnAbs (10-1074/PGDM1400/VRC07-523LS) as the best against clade C viruses and a combination of MPER/V3/CD4bs-targeting bnAbs (10E8v4/10-1074/VRC07-523LS) as the best against clade B viruses, due to low coverage of V2-glycan directed bnAbs against clade B viruses. Overall, the AMP placebo viruses represent a valuable resource for defining the sensitivity of contemporaneous circulating viral strains to bnAbs and highlight the need to update reference panels regularly. Our data also suggests that combining bnAbs in passive immunization trials would improve coverage of global viruses.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Lineage frequency time series reveal elevated levels of genetic drift in SARS-CoV-2 transmission in England

Genetic drift in infectious disease transmission results from randomness of transmission and host recovery or death. The strength of genetic drift for SARS-CoV-2 transmission is expected to be high due to high levels of superspreading, and this is expected to substantially impact disease epidemiology and evolution. However, we don’t yet have an understanding of how genetic drift changes over time or across locations. Furthermore, noise that results from data collection can potentially confound estimates of genetic drift. To address this challenge, we develop and validate a method to jointly infer genetic drift and measurement noise from time-series lineage frequency data. Our method is highly scalable to increasingly large genomic datasets, which overcomes a limitation in commonly used phylogenetic methods. We apply this method to over 490,000 SARS-CoV-2 genomic sequences from England collected between March 2020 and December 2021 by the COVID-19 Genomics UK (COG-UK) consortium and separately infer the strength of genetic drift for pre-B.1.177, B.1.177, Alpha, and Delta. We find that even after correcting for measurement noise, the strength of genetic drift is consistently, throughout time, higher than that expected from the observed number of COVID-19 positive individuals in England by 1 to 3 orders of magnitude, which cannot be explained by literature values of superspreading. Our estimates of genetic drift suggest low and time-varying establishment probabilities for new mutations, inform the parametrization of SARS-CoV-2 evolutionary models, and motivate future studies of the potential mechanisms for increased stochasticity in this system.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Virulence and Genetic Diversity of Puccinia spp., Causal Agents of Rust on Switchgrass (Panicum virgatum L.) in the USA

Switchgrass (Panicum virgatum L.) is an important cellulosic biofuel grass native to North America. Rust, caused by Puccinia spp. is the most predominant disease of switchgrass and has the potential to impact biomass conversion. In this study, virulence patterns were determined on a set of 38 switchgrass genotypes for 14 single-spore rust isolates from 14 field samples collected in seven states. Single nucleotide polymorphism (SNP) variation was also assessed in 720 sequenced cloned amplicons representing 654 base pairs of the elongation factor 1-α gene from the field samples. Five major haplotypes were identified differing by 11 out of the 39 SNP positions identified. STRUCTURE, Principal Coordinate Analysis, and phylogenetic analyses divided the rust population into two genetic clusters. Virginia and Georgia had the highest and lowest rust genetic diversity, respectively. Only nine accessions showed a differential disease response between the 14 isolates, allowing the identification of eight races, differing by 1–3 virulence factors. Overall, the results suggested clonal reproduction of the pathogen and a North–South differentiation via local adaptation. However, similar haplotypes and races were also recovered from several states, suggesting migration events, and highlighting the need to further investigate the switchgrass rust population structure and evolution in the USA.

Bahri, Bochra A. (ORCID:0000000159055880)↗
DOE OSTI2021

Methods and compositions for identification of source of microbial contamination in a sample

Herein are described 1058 different bacterial taxa that were unique to either human, grazing mammal, or bird fecal wastes. These identified taxa can serve as specific identifier taxa for these sources in environmental waters. Two field tests in marine waters demonstrate the capacity of phylogenetic microarray analysis to track multiple sources with one test.

Andersen, Gary L.↗
DOE OSTI2024

Description of Pegethrix niliensis sp. nov., a Novel Cyanobacterium from the Nile River Basin, Egypt: A Polyphasic Analysis and Comparative Study of Related Genera in the Oculatellales Order

In this paper, we examine the filamentous cyanobacterial strain NILCB16 and describe it as a new species within the genus Pegethrix. The original population was sampled from a mat growing in an irrigation canal in the Nile River, Egypt. Initially classified under Plectonema or Planktolyngbya, the strain is a potential producer of the toxins microcystin and β-N-Methylamino-L-Alanine (BMAA). Additionally, we reviewed the taxonomic relationships between the Oculatellales genera. To describe the new species, we conducted a polyphasic study, encompassing 16S rRNA gene phylogenetic analyses performed using both Maximum Likelihood and Bayesian methods, sequence identity (p-distance) analysis, 16S-23S ITS secondary structures, and morphological and habitat comparisons. The phylogenetic analysis revealed that strain NILCB16 clustered within the Pegethrix clade with strong phylogenetic support, but in a distinct position from other species in the genus. The strain shared a maximum 16S rRNA gene identity of 97.3% with P. qiandaoensis and 96.1% with the type species, P. bostrychoides. Morphologically, NILCB16 can be differentiated from other species in the genus by its lack of false branching. Our phylogenetic analyses also show that Pegethrix, Cartusia, Elainella, and Maricoleus are clustered with strong phylogenetic support. They exhibit high 16S rRNA gene identity and are morphologically indistinguishable, suggesting they could potentially be merged into a single genus in the future.

Hentschke, Guilherme Scotta (ORCID:000000034396024↗
DOE OSTI2021

Pseudodesulfovibrio mercurii sp. nov., a mercury-methylating bacterium isolated from sediment

The sulfate-reducing, mercury-methylating strain ND132 T was isolated from the brackish anaerobic bottom sediments of Chesapeake Bay, USA. Capable of high levels of mercury (Hg) methylation, ND132 T has been widely used as a model strain to study the process and to determine the genetic basis of Hg methylation. Originally called Desulfovibrio desulfuricans ND132 T on the basis of an early partial 16S rRNA sequence, the strain has never been formally described. Phylogenetic and physiological traits place this strain within the genus Pseudodesulfovibrio, in the recently reclassified phylum Desulfobacterota (formerly Deltaproteobacteria ). ND132 T is most closely related to Pseudodesulfovibrio hydrargyri BerOc1 T and Pseudodesulfovibrio indicus J2T. Analysis of average nucleotide identity (ANI) of whole-genome sequences showed roughly 88 % ANI between P. hydrargyri BerOc1T and ND132T, and 84 % similarity between ND132T and P. indicus J2 T . These cut-off scores <95 %, along with a multi-gene phylogenetic analysis of members of the family Desulfovibrionacea, and differences in physiology indicate that all three strains represent separate species. The Gram-stain-negative cells are vibrio-shaped, motile and not sporulated. ND132 T is a salt-tolerant mesophile with optimal growth in the laboratory at 32 °C, 2 % salinity, and pH 7.8. The DNA G+C content of the genomic DNA is 65.2 %. It is an incomplete oxidizer of short chain fatty acids, using lactate, pyruvate and fumarate with sulfate or sulfite as the terminal electron acceptors. ND132 T can respire fumarate using pyruvate as an electron donor. The major fatty acids are iso-C 15 :0 , anteiso-C 15 : 0 , iso-C 17 : 0 , iso-C 17 : 1 ω9c and anteiso-C 17 : 0 . We propose the classification of strain ND132 T (DSM 110689, ATCC TSD-224) as the type strain Pseudodesulfovibrio mercurii sp. nov.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Novel adaptive immune systems in pristine Antarctic soils

Antarctic environments are dominated by microorganisms, which are vulnerable to viral infection. Although several studies have investigated the phylogenetic repertoire of bacteria and viruses in these poly-extreme environments with freezing temperatures, high ultra violet irradiation levels, low moisture availability and hyper-oligotrophy, the evolutionary mechanisms governing microbial immunity remain poorly understood. Using genome-resolved metagenomics, we test the hypothesis that Antarctic poly-extreme high-latitude microbiomes harbour diverse adaptive immune systems. Our analysis reveals the prevalence of prophages in bacterial genomes (Bacteroidota and Verrucomicrobiota), suggesting the significance of lysogenic infection strategies in Antarctic soils. Furthermore, we demonstrate the presence of diverse CRISPR-Cas arrays, including Class 1 arrays (Types I-B, I-C, and I-E), alongside systems exhibiting novel gene architecture among their effector cas genes. Notably, a Class 2 system featuring type V variants lacks CRISPR arrays, encodes Cas1 and Cas2 adaptation module genes. Phylogenetic analysis of Cas12 effector proteins hints at divergent evolutionary histories compared to classified type V effectors and indicates that TnpB is likely the ancestor of Cas12 nucleases. Our findings suggest substantial novelty in Antarctic cas sequences, likely driven by strong selective pressures. These results underscore the role of viral infection as a key evolutionary driver shaping polar microbiomes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Biogeographic patterns in populations of marine Pseudoalteromonas atlantica isolates

Intra-specific genomic diversity is well documented in microbes. The question, however, remains whether natural selection or neutral evolution is the major contributor to this diversity. We undertook this study to estimate genomic diversity in Pseudoalteromonas atlantica populations and whether the diversity, if present, could be attributed to environmental factors or distance effects. Here, we isolated and sequenced twenty-three strains of P. atlantica from three geographically distant deep marine basins and performed comparative genomic analyses to study the genomic diversity of populations among these basins. Average nucleotide identity followed a strictly geographical pattern. In two out of three locations, the strains within the location exhibited >99.5% identity, whereas, among locations, the strains showed <98.11% identity. Phylogenetic and pan-genome analysis also reflected the biogeographical separation of the strains. Strains from the same location shared many accessory genes and clustered closely on the phylogenetic tree. Phenotypic diversity between populations was studied in ten out of twenty-three strains testing carbon and nitrogen source utilization and osmotolerance. A genetic basis for phenotypic diversity could be established in most cases but was apparently not influenced by local environmental conditions. Our study suggests that neutral evolution may have a substantial role in the biodiversity of P. atlantica.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

First Report and Molecular Variability of Belonolaimus longicaudatus Associated with Turfgrass in Maryland

Abstract Turfgrass is a crop used extensively in athletic fields and golf courses in Maryland. A soil sample collected in July 2023 from an athletic field in Baltimore County, Maryland, part of a turfgrass nematode survey, containedBelonolaimus longicaudatus. In the southeastern United States,B. longicaudatusis an economically important pathogen of warm season turfgrass. The density was four individuals/100 cm 3 of soil, and no visual symptoms were observed in the bermudagrass field. Morphological features and morphometrics of males and females were consistent withB. longicaudatusand placed the Maryland population in a subclade that was geographically represented by populations from north and west Florida, Texas, and South Carolina. Sequencing of the internal transcribed spacer region ITS1 and ITS2 and 28S large ribosomal subunit D2-23 expansion region confirmed the species' identity. Phylogenetic trees and parsimony network analysis placed the Maryland isolate in a large grouping ofB. longicaudatuspopulations including those from Alabama, Delaware, Florida, Indiana, Mississippi, South Carolina, and Texas. To our knowledge, this is the first report ofB. longicaudatusin Maryland.

Zoology↗
DOE OSTI2021

Whole-Genome SNP Analysis Identifies Putative Mycobacterium bovis Transmission Clusters in Livestock and Wildlife in Catalonia, Spain

The high-resolution WGS analyses of MTBC strains have provided useful insight for determining sources of infection for animal tuberculosis. In Spain, tuberculosis in livestock is caused by Mycobacterium bovis and Mycobacterium caprae, where wildlife reservoirs play an important role. We analyzed a set of 125 M. bovis isolates obtained from livestock and wildlife from Catalonia to investigate strain diversity and identify possible sources and/or causes of infection. Whole-genome SNP profiles were used for phylogenetic reconstruction and pairwise SNP distance analysis. Additionally, SNPs were investigated to identify virulence and antimicrobial resistance factors to investigate clade-specific associations. Putative transmission clusters (≤12 SNPs) were identified, and associated epidemiological metadata were used to determine possible explanatory factors for transmission. M. bovis distribution was heterogeneous, with 7 major clades and 21 putative transmission clusters. In order of importance, the explanatory factors associated were proximity and neighborhood, residual infection, livestock-wildlife interaction, shared pasture, and movement. Genes related to lipid transport and metabolism showed the highest number of SNPs. All isolates were pyrazinamide resistant, and five were additionally resistant to isoniazid, but no clade-specific associations could be determined. Our findings highlight the importance of high-resolution molecular surveillance to monitor bovine tuberculosis dynamics in a low-prevalence setting.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

A quantitative framework reveals ecological drivers of grassland microbial community assembly in response to warming

Abstract Unraveling the drivers controlling community assembly is a central issue in ecology. Although it is generally accepted that selection, dispersal, diversification and drift are major community assembly processes, defining their relative importance is very challenging. Here, we present a framework to quantitatively infer community assembly mechanisms by phylogenetic bin-based null model analysis (iCAMP). iCAMP shows high accuracy (0.93–0.99), precision (0.80–0.94), sensitivity (0.82–0.94), and specificity (0.95–0.98) on simulated communities, which are 10–160% higher than those from the entire community-based approach. Application of iCAMP to grassland microbial communities in response to experimental warming reveals dominant roles of homogeneous selection (38%) and ‘drift’ (59%). Interestingly, warming decreases ‘drift’ over time, and enhances homogeneous selection which is primarily imposed on Bacillales. In addition, homogeneous selection has higher correlations with drought and plant productivity under warming than control. iCAMP provides an effective and robust tool to quantify microbial assembly processes, and should also be useful for plant and animal ecology.

59 BASIC BIOLOGICAL SCIENCES↗