Integrated genomic and functional analyses of human skin-associated Staphylococcus reveal extensive inter- and intra-species diversity.

Human skin is stably colonized by a distinct microbiota that functions together with epidermal cells to maintain a protective physical barrier. Staphylococcus, a prominent genus of the skin microbiota, participates in colonization resistance, tissue repair, and host immune regulation in strain-specific manners. To unlock the potential of engineering skin microbial communities, we aim to characterize the diversity of this genus within the context of the skin environment. We reanalyzed an extant 16S rRNA amplicon dataset obtained from distinct body sites of healthy volunteers, providing a detailed biogeographic depiction of staphylococcal species that colonize our skin. S. epidermidis, S. capitis, and S. hominis were the most abundant staphylococcal species present in all volunteers and were detected at all body sites. Pan-genome analysis of isolates from these three species revealed that the genus-core was dominated by central metabolism genes. Species-restricted-core genes encoded known host colonization functions. The majority (~68%) of genes were detected only in a fraction of isolate genomes, underscoring the immense strain-specific gene diversity. Conspecific genomes grouped into phylogenetic clades, exhibiting body site preference. Each clade was enriched for distinct gene sets that are potentially involved in site tropism. Finally, we conducted gene expression studies of select isolates showing variable growth phenotypes in skin-like medium. In vitro expression revealed extensive intra- and inter-species gene expression variation, substantially expanding the functional diversification within each species. Our study provides an important resource for future ecological and translational studies to examine the role of shared and strain-specific staphylococcal genes within the skin environment.

Chromosome-scale haplotype-resolved pangenomics.

Complete pangenomics is crucial for understanding genetic diversity and evolution across the tree of life. Chromosome-scale, haplotype-resolved pangenomics allows complex structural variations, long-range interactions, and associated functions to be discerned in species populations. We explore the need for high-resolution pangenomes, discuss computational strategies for their development, and describe applications in biodiversity and human health.

Systems biology approach to functionally assess the Clostridioides difficile pangenome reveals genetic diversity with discriminatory power.

Combatting Clostridioides difficile infections, a dominant cause of hospital-associated infections with incidence and resulting deaths increasing worldwide, is complicated by the frequent emergence of new virulent strains. Here, we employ whole-genome sequencing, high-throughput phenotypic screenings, and genome-scale models of metabolism to evaluate the genetic diversity of 451 strains of C. difficile. Constructing the C. difficile pangenome based on this set revealed 9,924 distinct gene clusters, of which 2,899 (29%) are defined as core, 2,968 (30%) are defined as unique, and the remaining 4,057 (41%) are defined as accessory. We develop a strain typing method, sequence typing by accessory genome (STAG), that identifies 176 genetically distinct groups of strains and allows for explicit interrogation of accessory gene content. Thirty-five strains representative of the overall set were experimentally profiled on 95 different nutrient sources, revealing 26 distinct growth profiles and unique nutrient preferences; 451 strain-specific genome scale models of metabolism were constructed, allowing us to computationally probe phenotypic diversity in 28,864 unique conditions. The models create a mechanistic link between the observed phenotypes and strain-specific genetic differences and exhibit an ability to correctly predict growth in 76% of measured cases. The typing and model predictions are used to identify and contextualize discriminating genetic features and phenotypes that may contribute to the emergence of new problematic strains.

PPanG: a precision pangenome browser enabling nucleotide-level analysis of genomic variations in individual genomes and their graph-based pangenome.

Graph-based pangenome is gaining more popularity than linear pangenome because it stores more comprehensive information of variations. However, traditional linear genome browser has its own advantages, especially the tremendous resources accumulated historically. With the fast-growing number of individual genomes and their annotations available, the demand for a genome browser to visualize genome annotation for many individuals together with a graph-based pangenome is getting higher and higher. Here we report a new pangenome browser PPanG, a precise pangenome browser enabling nucleotide-level comparison of individual genome annotations together with a graph-based pangenome. Nine rice genomes with annotations were provided by default as potential references, and any individual genome can be selected as the reference. Our pangenome browser provides unprecedented insights on genome variations at different levels from base to gene, and reveals how the structures of a gene could differ for individuals. PPanG can be applied to any species with multiple individual genomes available and it is available at https://cgm.sjtu.edu.cn/PPanG .

Critical assessment of pan-genomic analysis of metagenome-assembled genomes.

Pan-genome analyses of metagenome-assembled genomes (MAGs) may suffer from the known issues with MAGs: fragmentation, incompleteness and contamination. Here, we conducted a critical assessment of pan-genomics of MAGs, by comparing pan-genome analysis results of complete bacterial genomes and simulated MAGs. We found that incompleteness led to significant core gene (CG) loss. The CG loss remained when using different pan-genome analysis tools (Roary, BPGA, Anvi'o) and when using a mixture of MAGs and complete genomes. Contamination had little effect on core genome size (except for Roary due to in its gene clustering issue) but had major influence on accessory genomes. Importantly, the CG loss was partially alleviated by lowering the CG threshold and using gene prediction algorithms that consider fragmented genes, but to a less degree when incompleteness was higher than 5%. The CG loss also led to incorrect pan-genome functional predictions and inaccurate phylogenetic trees. Our main findings were supported by a study of real MAG-isolate genome data. We conclude that lowering CG threshold and predicting genes in metagenome mode (as Anvi'o does with Prodigal) are necessary in pan-genome analysis of MAGs. Development of new pan-genome analysis tools specifically for MAGs are needed in future studies.

High genetic diversity and different type VI secretion systems in Enterobacter species revealed by comparative genomics analysis.

The human-pathogenic Enterobacter species are widely distributed in diverse environmental conditions, however, the understanding of the virulence factors and genetic variations within the genus is very limited. In this study, we performed comparative genomics analysis of 49 strains originated from diverse niches and belonged to eight Enterobacter species, in order to further understand the mechanism of adaption to the environment in Enterobacter. The results showed that they had an open pan-genome and high genomic diversity which allowed adaptation to distinctive ecological niches. We found the number of secretion systems was the highest among various virulence factors in these Enterobacter strains. Three types of T6SS gene clusters including T6SS-A, T6SS-B and T6SS-C were detected in most Enterobacter strains. T6SS-A and T6SS-B shared 13 specific core genes, but they had different gene structures, suggesting they probably have different biological functions. Notably, T6SS-C was restricted to E. cancerogenus. We detected a T6SS gene cluster, highly similar to T6SS-C (91.2%), in the remote related Citrobacter rodenitum, suggesting that this unique gene cluster was probably acquired by horizontal gene transfer. The genomes of Enterobacter strains possess high genetic diversity, limited number of conserved core genes, and multiple copies of T6SS gene clusters with differentiated structures, suggesting that the origins of T6SS were not by duplication instead by independent acquisition. These findings provide valuable information for better understanding of the functional features of Enterobacter species and their evolutionary relationships.

Comparative genomic analysis of clinical Enterococcus faecalis distinguishes strains isolated from the bladder.

BACKGROUND: Enterococcus faecalis is the most commonly isolated enterococcal species in clinical infection. This bacterium is notorious for its ability to share genetic content within and outside of its species. With this increased proficiency for horizontal gene transfer, tremendous genomic diversity within this species has been identified. Many researchers have hypothesized E. faecalis exhibits niche adaptation to establish infections or colonize various parts of the human body. Here, we hypothesize that E. faecalis strains isolated from the human bladder will carry unique genomic content compared to clinical strains isolated from other sources. RESULTS: This analysis includes comparison of 111 E. faecalis genomes isolated from bladder, urogenital, blood, and fecal samples. Phylogenomic comparison shows no association between isolation source and lineage; however, accessory genome comparison differentiates blood and bladder genomes. Further gene enrichment analysis identifies gene functions, virulence factors, antibiotic resistance genes, and plasmid-associated genes that are enriched or rare in bladder genomes compared to urogenital, blood, and fecal genomes. Using these findings as training data and 682 publicly available genomes as test data, machine learning classifiers successfully distinguished between bladder and non-bladder strains with high accuracy. Genes identified as important for this differentiation were often related to transposable elements and phage, including 3 prophage species found almost exclusively in bladder and urogenital genomes. CONCLUSIONS: E. faecalis strains isolated from the bladder contain unique genomic content when compared to strains isolated from other body sites. This genomic diversity is most likely due to horizontal gene transfer, as evidenced by lack of phylogenomic clustering and enrichment of transposable elements and prophages. Investigation into how these enriched genes influence host-microbe interactions may elucidate gene functions required for successful bladder colonization and disease establishment.

Pangenomics Comes of Age: From Bacteria to Plant and Animal Applications.

The pangenome refers to a collection of genomic sequence found in the entire species or population rather than in a single individual; the sequence can be core, present in all individuals, or accessory (variable or dispensable), found in a subset of individuals only. While pangenomic studies were first undertaken in bacterial species, developments in genome sequencing and assembly approaches have allowed construction of pangenomes for eukaryotic organisms, fungi, plants, and animals, including two large-scale human pangenome projects. Analysis of the these pangenomes revealed key differences, most likely stemming from divergent evolutionary histories, but also surprising similarities.

Diversity at single nucleotide to pangenome scales among sulfur cycling bacteria in salt marshes.

IMPORTANCE: Salt marshes are known for their significant carbon storage capacity, and sulfur cycling is closely linked with the ecosystem-scale carbon cycling in these ecosystems. Sulfate reducers are key for the decomposition of organic matter, and sulfur oxidizers remove toxic sulfide, supporting the productivity of marsh plants. To date, the complexity of coastal environments, heterogeneity of the rhizosphere, high microbial diversity, and uncultured majority hindered our understanding of the genomic diversity of sulfur-cycling microbes in salt marshes. Here, we use comparative genomics to overcome these challenges and provide an in-depth characterization of sulfur-cycling microbial diversity in salt marshes. We characterize communities across distinct sites and plant species and uncover extensive genomic diversity at the taxon level and specific genomic features present in MAGs affiliated with uncultivated sulfur-cycling lineages. Our work provides insights into the partnerships in salt marshes and a roadmap for multiscale analyses of diversity in complex biological systems.

Mining therapeutic targets from the antibiotic-resistant Campylobacter coli and virtual screening of natural product inhibitors against its riboflavin synthase.

Campylobacter coli resides in the intestine of several commonly consumed animals, as well as water and soil. It leads to campylobacteriosis when humans eat raw/undercooked meat or come into contact with infected animals. A common manifestation of the infection is fever, nausea, headache, and diarrhea. Increasing antibiotic resistance is being observed in this pathogen. The increased incidence of C. coli infection, and post-infection complications like Guillain-Barré syndrome, make it an important pathogen. It is essential to find novel therapeutic targets and drugs against it, especially with the emergence of antibiotic-resistant strains. In the current study, genomes of 89 antibiotic-resistant strains of C. coli were downloaded from the PATRIC database. Potent drug targets (n = 36) were prioritized from the core genome (n = 1,337 genes) of this species. Riboflavin synthase was selected as a drug target and pharmacophore-based virtual screening was performed to predict its inhibitors from the NPASS (n = ~ 30,000 compounds) natural product library. The top three docked compounds (NPC115144, NPC307895, and NPC470462) were selected for dynamics simulation (for 50 ns) and ADMET profiling. These identified compounds appear safe for targeting this pathogen and can be further validated by experimental analysis before clinical trials.

GenAPI: a tool for gene absence-presence identification in fragmented bacterial genome sequences.

BACKGROUND: Bacterial gene loss and acquisition is a well-known phenomenon which contributes to bacterial adaptation through changes in important phenotypes such as virulence, antibiotic resistance and metabolic capability. While advances in DNA sequencing have accelerated our ability to generate short genome sequence reads to disentangle phenotypic changes caused by gene loss and acquisition, the short-read genome sequencing often results in fragmented genome assemblies as a basis for identification of gene loss and acquisition events. However, sensitive and precise determination of gene content change for fragmented genome assemblies remains challenging as analysis needs to account for cases when only a fragment of the gene is assembled or when the gene assembly is split in more than one contig. RESULTS: We developed GenAPI, a command-line tool that is designed to compare the gene content of bacterial genomes for which only fragmented genome assemblies are available. GenAPI, unlike other available tools of similar purpose, accounts for imperfections in sequencing and assembly, and aims to compensate for them. We tested the performance of GenAPI on three different datasets to show that GenAPI has a high sensitivity while it maintains precision when dealing with partly assembled genes in both simulated and real datasets. Furthermore, we benchmarked the performance of GenAPI with six popular tools for gene presence-absence identification. CONCLUSIONS: Our developed bioinformatics tool, called GenAPI, has the same precision and recall rates when analyzing complete genome sequences as the other tools of the same purpose; however, GenAPI's performance is markedly better on fragmented genome assemblies.

Assessing graph-based read mappers against a baseline approach highlights strengths and weaknesses of current methods.

BACKGROUND: Graph-based reference genomes have become popular as they allow read mapping and follow-up analyses in settings where the exact haplotypes underlying a high-throughput sequencing experiment are not precisely known. Two recent papers show that mapping to graph-based reference genomes can improve accuracy as compared to methods using linear references. Both of these methods index the sequences for most paths up to a certain length in the graph in order to enable direct mapping of reads containing common variants. However, the combinatorial explosion of possible paths through nearby variants also leads to a huge search space and an increased chance of false positive alignments to highly variable regions. RESULTS: We here assess three prominent graph-based read mappers against a hybrid baseline approach that combines an initial path determination with a tuned linear read mapping method. We show, using a previously proposed benchmark, that this simple approach is able to improve overall accuracy of read-mapping to graph-based reference genomes. CONCLUSIONS: Our method is implemented in a tool Two-step Graph Mapper, which is available at https://github.com/uio-bmi/two_step_graph_mapperalong with data and scripts for reproducing the experiments. Our method highlights characteristics of the current generation of graph-based read mappers and shows potential for improvement for future graph-based read mappers.

Comparative genome analysis of arsenic reducing, hydrocarbon metabolizing groundwater bacterium Achromobacter sp. KAs 3-5T explains its competitive edge for survival in aquifer environment.

Whole genome sequence of arsenic (As) reducing, hydrocarbon metabolizing groundwater bacterium Achromobacter sp. KAs 3-5T was explored to understand the genomic basis of its As-ecophysiology and niche adaptation in aquifer environment. The genome (5.6 Mbp, 65.5 G + C mol %) encodes 4840 proteins, 1138 enzymes, 53 tRNAs, 11 rRNAs, 608 signal peptides, and 1.13% horizontally transferred genes. Presence of genes encoding cytosolic As5+-reduction (arsRCBH, ACR3), aromatics utilization (bph, naph, catABC, boxABCD, genACB), Fe-transformation (tonB, achromobactin, FUR, FeR), and denitrification (nar, nap) processes were observed and validated through proteomics. Phylogenomic analysis (< 90% ANI, < 50% DDH) confirmed strain KAs 3-5T to be a novel representative of the genus Achromobacter. An asymptotic open pan-genome (20,855 genes) and high correlation between genomic and ecological diversity suggested niche preference ability of this genus. Assemblage of species specific genes affiliated to transcription-regulation, membrane transport, and redox-transformation explained the strain's competitive survival strategies in As-rich oligotrophic groundwater.

Variation in abundance of predicted resistance genes in the Brassica oleracea pangenome.

Brassica oleracea is an important agricultural species encompassing many vegetable crops including cabbage, cauliflower, broccoli and kale; however, it can be susceptible to a variety of fungal diseases such as clubroot, blackleg, leaf spot and downy mildew. Resistance to these diseases is meditated by specific disease resistance genes analogs (RGAs) which are differently distributed across B. oleracea lines. The sequenced reference cultivar does not contain all B. oleracea genes due to gene presence/absence variation between individuals, which makes it necessary to search for RGA candidates in the B. oleracea pangenome. Here we present a comparative analysis of RGA candidates in the pangenome of B. oleracea. We show that the presence of RGA candidates differs between lines and suggests that in B. oleracea, SNPs and presence/absence variation drive RGA diversity using separate mechanisms. We identified 59 RGA candidates linked to Sclerotinia, clubroot, and Fusarium wilt resistance QTL, and these findings have implications for crop breeding in B. oleracea, which may also be applicable in other crops species.

Strain-Level Diversity Analysis of Pseudomonas fragi after In Situ Pangenome Reconstruction Shows Distinctive Spoilage-Associated Metabolic Traits Clearly Selected by Different Storage Conditions.

Microbial spoilage of raw meat causes huge economic losses every year. An understanding of the microbial ecology associated with the spoilage and its dynamics during the refrigerated storage of meat can help in preventing and delaying the spoilage-related activities. The raw meat microbiota is usually complex, but only a few members will develop during storage and cause spoilage upon the pressure from several external factors, such as temperature and oxygen availability. We characterized the metagenome of beef packed aerobically or under vacuum during refrigerated storage to explore how different packaging conditions may influence the microbial composition and potential spoilage-associated activities. Different population dynamics and spoilage-associated genomic repertoires occurred in beef stored aerobically or in vacuum packaging. Moreover, the pangenomes of Pseudomonas fragi strains were extracted from metagenomes. We demonstrated the presence of specific, storage-driven strain-level profiles of Pseudomonas fragi, characterized by different gene repertoires and thus potentially able to act differently during meat spoilage. The results provide new knowledge on strain-level microbial ecology associated with meat spoilage and may be of value for future strategies of spoilage prevention and food waste reduction.IMPORTANCE This work provides insights on the mechanisms involved in raw beef spoilage during refrigerated storage and on the selective pressure exerted by the packaging conditions. We highlighted the presence of different microbial metagenomes during the spoilage of beef packaged aerobically or under vacuum. The packaging condition was able to select specific Pseudomonas fragi strains with distinctive genomic repertoires. This study may help in deciphering the behavior of different biomes directly in situ in food and in understanding the specific contribution of different strains to food spoilage.

Molecular and Genomic Characterization of PFAB2: A Non-virulent Bacillus anthracis Strain Isolated from an Indian Hot Spring.

BACKGROUND: Thermophilic bacilli in both aerobic or facultative anaerobic forms have been isolated for over a hundred years from different mesophilic or thermophilic environments as they are potential source of bioactive secondary metabolites. But the taxonomic resolution in the Bacillus genus at species or at strain level is very challenging for the insufficient divergence of the 16S rRNA genes. One such recurring problem is among Bacillus anthracis, B. cereus and B. thuringiensis. The disease-causing B. anthracis strains have their characteristic virulence factors coded in two well-known plasmids, namely pXO1 (toxin genes) and pXO2 (capsule genes). OBJECTIVE: The present study aimed at the molecular and genomic characterization of a recently reported thermophilic and environmental isolate of B. anthracis, strain PFAB2. METHODS: We performed comparative genomics between the PFAB2 genome and different strains of B. anthracis, along with closely related B. cereus strains. RESULTS: The pangenomic analysis suggests that the PFAB2 genome harbors no complete prophage genes. Cluster analysis of Bray-Kurtis similarity resemblance matrix revealed that gene content of PFAB2 is more closely related to other environmental strains of B. anthracis. The secretome analysis and the in vitro and in vivo pathogenesis experiments corroborate the avirulent phenotype of this strain. The most probable explanation for this phenotype is the apparent absence of plasmids harboring genes for capsule biosynthesis and toxins secretion in the draft genome. Additional features of PFAB2 are good spore-forming and germinating capabilities and rapid replication ability. CONCLUSION: The high replication rate in a wide range of temperatures and culture media, the non-pathogenicity, the good spore forming capability and its genomic similarity to the Ames strain together make PFAB2 an interesting model strain for the study of the pathogenic evolution of B. anthracis.

PGAP-X: extension on pan-genome analysis pipeline.

BACKGROUND: Since PGAP (pan-genome analysis pipeline) was published in 2012, it has been widely employed in bacterial genomics research. Though PGAP has integrated several modules for pan-genomics analysis, how to properly and effectively interpret and visualize the results data is still a challenge. RESULT: To well present bacterial genomic characteristics, a novel cross-platform software was developed, named PGAP-X. Four kinds of data analysis modules were developed and integrated: whole genome sequences alignment, orthologous genes clustering, pan-genome profile analysis, and genetic variants analysis. The results from these analyses can be directly visualized in PGAP-X. The modules for data visualization in PGAP-X include: comparison of genome structure, gene distribution by conservation, pan-genome profile curve and variation on genic and genomic region. Meanwhile, result data produced by other programs with similar function can be imported to be further analyzed and visualized in PGAP-X. To test the performance of PGAP-X, we comprehensively analyzed 14 Streptococcus pneumonia strains and 14 Chlamydia trachomatis. The results show that, S. pneumonia strains have higher diversity on genome structure and gene contents than C. trachomatis strains. In addition, S. pneumonia strains might have suffered many evolutionary events, such genomic rearrangements, frequent horizontal gene transfer, homologous recombination, and other evolutionary process. CONCLUSION: Briefly, PGAP-X directly presents the characteristics of bacterial genomic diversity with different visualization methods, which could help us to intuitively understand dynamics and evolution in bacterial genomes. The source code and the pre-complied executable programs are freely available from http://pgapx.ybzhao.com .

From cultured to uncultured genome sequences: metagenomics and modeling microbial ecosystems.

Microorganisms and the viruses that infect them are the most numerous biological entities on Earth and enclose its greatest biodiversity and genetic reservoir. With strength in their numbers, these microscopic organisms are major players in the cycles of energy and matter that sustain all life. Scientists have only scratched the surface of this vast microbial world through culture-dependent methods. Recent developments in generating metagenomes, large random samples of nucleic acid sequences isolated directly from the environment, are providing comprehensive portraits of the composition, structure, and functioning of microbial communities. Moreover, advances in metagenomic analysis have created the possibility of obtaining complete or nearly complete genome sequences from uncultured microorganisms, providing important means to study their biology, ecology, and evolution. Here we review some of the recent developments in the field of metagenomics, focusing on the discovery of genetic novelty and on methods for obtaining uncultured genome sequences, including through the recycling of previously published datasets. Moreover we discuss how metagenomics has become a core scientific tool to characterize eco-evolutionary patterns of microbial ecosystems, thus allowing us to simultaneously discover new microbes and study their natural communities. We conclude by discussing general guidelines and challenges for modeling the interactions between uncultured microorganisms and viruses based on the information contained in their genome sequences. These models will significantly advance our understanding of the functioning of microbial ecosystems and the roles of microbes in the environment.

Measuring, visualizing and diagnosing reference bias with biastools.

Many bioinformatics methods seek to reduce reference bias, but no methods exist to comprehensively measure it. Biastools analyzes and categorizes instances of reference bias. It works in various scenarios, i.e. (a) when the donor's variants are known and reads are simulated, (b) when donor variants are known and reads are real, and (c) when variants are unknown and reads are real. Using biastools, we observe that more inclusive graph genomes result in fewer biased sites. We find that end-to-end alignment reduces bias at indels relative to local aligners. Finally, we use biastools to characterize how T2T references improve large-scale bias.

Measuring, visualizing, and diagnosing reference bias with biastools.

Many bioinformatics methods seek to reduce reference bias, but no methods exist to comprehensively measure it. Biastools analyzes and categorizes instances of reference bias. It works in various scenarios: when the donor's variants are known and reads are simulated; when donor variants are known and reads are real; and when variants are unknown and reads are real. Using biastools, we observe that more inclusive graph genomes result in fewer biased sites. We find that end-to-end alignment reduces bias at indels relative to local aligners. Finally, we use biastools to characterize how T2T references improve large-scale bias.