Designing function-specific minimal microbiomes from large microbial communities.

Microorganisms exist in large communities of diverse species, exhibiting various functionalities. The mammalian gut microbiome, for instance, has the functionality of digesting dietary fibre and producing different short-chain fatty acids. Not all microbes present in a community contribute to a given functionality; it is possible to find a minimal microbiome, which is a subset of the large microbiome, that is capable of performing the functionality while maintaining other community properties such as growth rate and metabolite production. Such a minimal microbiome will also contain keystone species for SCFA production in that community. In this work, we present a systematic constraint-based approach to identify a minimal microbiome from a large community for a user-proposed function. We employ a top-down approach with sequential deletion followed by solving a mixed-integer linear programming problem with the objective of minimising the L1-norm of the membership vector. Notably, we consider quantitative measures of community growth rate and metabolite production rates. We demonstrate the utility of our algorithm by identifying the minimal microbiomes corresponding to three model communities of the gut, and discuss their validity based on the presence of the keystone species in the community. Our approach is generic, flexible and finds application in studying a variety of microbial communities. The algorithm is available from https://github.com/RamanLab/minMicrobiome .

Quorum sensing in bacteria: in silico protein analysis, ecophysiology, and reconstruction of their evolutionary history.

BACKGROUND: Quorum sensing (QS) is a sophisticated cell-to-cell signalling mechanism that allows the coordination of important processes in microbial populations. The AI-1 and AI-2 autoinducer systems are among the best characterized bacterial QS systems at the genetic level. RESULTS: In this study, we present data derived from in silico screening of QS proteins from bacterial genomes available in public databases. Sequence analyses allowed identifying candidate sequences of known QS systems that were used to build phylogenetic trees. Eight categories were established according to the number of genes from the two major QS systems present in each genome, revealing a correlation with specific taxa, lifestyles or metabolic traits. Many species had incomplete QS systems, encoding the receptor protein but not the biosynthesis of the quorum sensing molecule (QSMs). Reconstruction of the evolutionary history of the LuxR family and prediction of the 3D structure of the ancestral protein suggested their monomeric configuration in the absence of the signal molecule and the presence of a cavity for its binding. CONCLUSIONS: Here we correlate the taxonomic affiliation and lifestyle of bacteria from different genera with the QS systems encoded in their genomes. Moreover, we present the first ancestral reconstruction of the LuxR QS receptors, providing further insight in their evolutionary history.

Direct metagenomics investigation of non-surgical hard-to-heal wounds: a review.

BACKGROUND: Non-surgical chronic wounds, including diabetes-related foot diseases (DRFD), pressure injuries (PIs) and venous leg ulcers (VLU), are common hard-to-heal wounds. Wound evolution partly depends on microbial colonisation or infection, which is often confused by clinicians, thereby hampering proper management. Current routine microbiology investigation of these wounds is based on in vitro culture, focusing only on a limited panel of the most frequently isolated bacteria, leaving a large part of the wound microbiome undocumented. METHODS: A literature search was conducted on original studies published through October 2022 reporting metagenomic next generation sequencing (mNGS) of chronic wound samples. Studies were eligible for inclusion if they applied 16 S rRNA metagenomics or shotgun metagenomics for microbiome analysis or diagnosis. Case reports, prospective, or retrospective studies were included. However, review articles, animal studies, in vitro model optimisation, benchmarking, treatment optimisation studies, and non-clinical studies were excluded. Articles were identified in PubMed, Google Scholar, Web of Science, Microsoft Academic, Crossref and Semantic Scholar databases. RESULTS: Of the 3,202 articles found in the initial search, 2,336 articles were removed after deduplication and 834 articles following title and abstract screening. A further 14 were removed after full text reading, with 18 articles finally included. Data were provided for 3,628 patients, including 1,535 DRFDs, 956 VLUs, and 791 PIs, with 164 microbial genera and 116 species identified using mNGS approaches. A high microbial diversity was observed depending on the geographical location and wound evolution. Clinically infected wounds were the most diverse, possibly due to a widespread colonisation by pathogenic bacteria from body and environmental microbiota. mNGS data identified the presence of virus (EBV) and fungi (Candida and Aspergillus species), as well as Staphylococcus and Pseudomonas bacteriophages. CONCLUSION: This study highlighted the benefit of mNGS for time-effective pathogen genome detection. Despite the majority of the included studies investigating only 16 S rDNA, ignoring a part of viral, fungal and parasite colonisation, mNGS detected a large number of bacteria through the included studies. Such technology could be implemented in routine microbiology for hard-to-heal wound microbiota investigation and post-treatment wound colonisation surveillance.

Cultivable epiphytic bacteria of the Chlorophyta Ulva sp.: diversity, antibacterial, and biofilm-modulating activities.

AIMS: Macroalgae harbor a rich epiphytic microbiota that plays a crucial role in algal morphogenesis and defense mechanisms. This study aims to isolate epiphytic cultivable microbiota from Ulva sp. surfaces. Various culture media were employed to evaluate a wide range of cultivable microbiota. Our objective was to assess the antibacterial and biofilm-modulating activities of supernatants from isolated bacteria. METHODS AND RESULTS: Sixty-nine bacterial isolates from Ulva sp. were identified based on 16S rRNA gene sequencing. Their antibacterial activity and biofilm modulation potential were screened against three target marine bacteria: 45%, mostly affiliated with Gammaproteobacteria and mainly grown on diluted R2A medium (R2Ad), showed strong antibacterial activity, while 18% had a significant impact on biofilm modulation. Molecular network analysis was carried out on four bioactive bacterial supernatants, revealing new molecules potentially responsible for their activities. CONCLUSION: R2Ad offered the greatest diversity and proportion of active isolates. The molecular network approach holds promise for both identifying bacterial isolates based on their molecular production and characterizing antibacterial and biofilm-modulating activities.

Diversity and Functionality of Bacteria Associated with Different Tissues of Spider Heteropoda venatoria Revealed through Integration of High-Throughput Sequencing and Culturomics Approaches.

Spiders host a diverse range of bacteria in their guts and other tissues, which have been found to play a significant role in their fitness. This study aimed to investigate the community diversity and functional characteristics of spider-associated bacteria in four tissues of Heteropoda venatoria using HTS of the 16S rRNA gene and culturomics technologies, as well as the functional verification of the isolated strains. The results of HTS showed that the spider-associated bacteria in different tissues belonged to 34 phyla, 72 classes, 170 orders, 277 families, and 458 genera. Bacillus was found to be the most abundant bacteria in the venom gland, silk gland, and ovary, while Stenotrophomonas, Acinetobacter, and Sphingomonas were dominant in the gut microbiota. Based on the amplicon sequencing results, 21 distinct cultivation conditions were developed using culturomics to isolate bacteria from the ovary, gut, venom gland, and silk gland. A total of 119 bacterial strains, representing 4 phyla and 25 genera, with Bacillus and Serratia as the dominant genera, were isolated. Five strains exhibited high efficiency in degrading pesticides in the in vitro experiments. Out of the 119 isolates, 28 exhibited antibacterial activity against at least one of the tested bacterial strains, including the pathogenic bacteria Staphylococcus aureus, Acinetobacter baumanii, and Enterococcus faecalis. The study also identified three strains, GL312, PL211, and PL316, which exhibited significant cytotoxicity against MGC-803. The crude extract from the fermentation broth of strain PL316 was found to effectively induce apoptosis in MGC-803 cells. Overall, this study offers a comprehensive understanding of the bacterial community structure associated with H. venatoria. It also provides valuable insights into discovering novel antitumor natural products for gastric cancer and xenobiotic-degrading bacteria of spiders.

Genetic recombination-mediated evolutionary interactions between phages of potential industrial importance and prophages of their hosts within or across the domains of Escherichia, Listeria, Salmonella, Campylobacter, and Staphylococcus.

BACKGROUND: The in-depth understanding of the role of lateral genetic transfer (LGT) in phage-prophage interactions is essential to rationalizing phage applications for human and animal therapy, as well as for food and environmental safety. This in silico study aimed to detect LGT between phages of potential industrial importance and their hosts. METHODS: A large array of genetic recombination detection algorithms, implemented in SplitsTree and RDP4, was applied to detect LGT between various Escherichia, Listeria, Salmonella, Campylobacter, Staphylococcus, Pseudomonas, and Vibrio phages and their hosts. PHASTER and RAST were employed respectively to identify prophages across the host genome and to annotate LGT-affected genes with unknown functions. PhageAI was used to gain deeper insights into the life cycle history of recombined phages. RESULTS: The split decomposition inferences (bootstrap values: 91.3-100; fit: 91.433-100), coupled with the Phi (0.0-2.836E-12) and RDP4 (P being well below 0.05) statistics, provided strong evidence for LGT between certain Escherichia, Listeria, Salmonella, and Campylobacter virulent phages and prophages of their hosts. The LGT events entailed mainly the phage genes encoding for hypothetical proteins, while some of these genetic loci appeared to have been affected even by intergeneric recombination in specific E. coli and S. enterica virulent phages when interacting with their host prophages. Moreover, it is shown that certain L. monocytogenes virulent phages could serve at least as the donors of the gene loci, involved in encoding for the basal promoter specificity factor, for L. monocytogenes. In contrast, the large genetic clusters were determined to have been simultaneously exchanged by many S. aureus prophages and some Staphylococcus temperate phages proposed earlier as potential therapeutic candidates (in their native or modified state). The above genetic clusters were found to encompass multiple genes encoding for various proteins, such as e.g., phage tail proteins, the capsid and scaffold proteins, holins, and transcriptional terminator proteins. CONCLUSIONS: It is suggested that phage-prophage interactions, mediated by LGT (including intergeneric recombination), can have a far-reaching impact on the co-evolutionary trajectories of industrial phages and their hosts especially when excessively present across microbially rich environments.

Uncovering specific taxonomic and functional alteration of gut microbiota in chronic kidney disease through 16S rRNA data.

Introduction: Chronic kidney disease (CKD) is worldwide healthcare burden with growing incidence and death rate. Emerging evidence demonstrated the compositional and functional differences of gut microbiota in patients with CKD. As such, gut microbial features can be developed as diagnostic biomarkers and potential therapeutic target for CKD. Methods: To eliminate the outcome bias arising from factors such as geographical distribution, sequencing platform, and data analysis techniques, we conducted a comprehensive analysis of the microbial differences between patients with CKD and healthy individuals based on multiple samples worldwide. A total of 980 samples from six references across three nations were incorporated from the PubMed, Web of Science, and GMrepo databases. The obtained 16S rRNA microbiome data were subjected to DADA2 processing, QIIME2 and PICRUSt2 analyses. Results: The gut microbiota of patients with CKD differs significantly from that of healthy controls (HC), with a substantial decrease in the microbial diversity among the CKD group. Moreover, a significantly reduced abundance of bacteria Faecalibacterium prausnitzii (F. prausnitzii) was detected in the CKD group through linear discriminant analysis effect size (LEfSe) analysis, which may be associated with the alleviating effects against CKD. Notably, we identified CKD-depleted F. prausnitzii demonstrated a significant negative correlation with three pathways based on predictive functional analysis, suggesting its potential role in regulating systemic acidbase disturbance and pro-oxidant metabolism. Discussion: Our findings demonstrated notable alterations of gut microbiota in CKD patients. Specific gut-beneficial microbiota, especially F. prausnitzii, may be developed as a preventive and therapeutic tool for CKD clinical management.

Amino acid bites: Microbial snacking influences host metabolism.

The gut microbiota has the capacity to metabolize food-derived molecules. In this issue of Cell Host & Microbe, Li et al. explore how some bacterial species of the gut microbiota can deplete amino acids in the gut lumen, modulating the amino acid landscape and energy metabolism of the host.

Debugging neurodevelopment disorders.

Gut bacteria are thought to contribute to neurodevelopmental disorders, but whether they are causal or predictive of disease remains unclear. In a prospective longitudinal study of thousands of children, Ahrens et al. generate evidence for the role of the gut microbiome in neurodevelopmental disorders while highlighting important open questions.

Establishment of a Multiplex Detection Method for Common Bacteria in Blood Based on Human Mannan-Binding Lectin Protein-Conjugated Magnetic Bead Enrichment Combined with Recombinase-Aided PCR Technology.

Objective: Recombinase-aided polymerase chain reaction (RAP) is a sensitive, single-tube, two-stage nucleic acid amplification method. This study aimed to develop an assay that can be used for the early diagnosis of three types of bacteremia caused by Staphylococcus aureus (SA), Pseudomonas aeruginosa (PA), and Acinetobacter baumannii (AB) in the bloodstream based on recombinant human mannan-binding lectin protein (M1 protein)-conjugated magnetic bead (M1 bead) enrichment of pathogens combined with RAP. Methods: Recombinant plasmids were used to evaluate the assay sensitivity. Common blood influenza bacteria were used for the specific detection. Simulated and clinical plasma samples were enriched with M1 beads and then subjected to multiple recombinase-aided PCR (M-RAP) and quantitative PCR (qPCR) assays. Kappa analysis was used to evaluate the consistency between the two assays. Results: The M-RAP method had sensitivity rates of 1, 10, and 1 copies/µL for the detection of SA, PA, and AB plasmids, respectively, without cross-reaction to other bacterial species. The M-RAP assay obtained results for < 10 CFU/mL pathogens in the blood within 4 h, with higher sensitivity than qPCR. M-RAP and qPCR for SA, PA, and AB yielded Kappa values of 0.839, 0.815, and 0.856, respectively ( P < 0.05). Conclusion: An M-RAP assay for SA, PA, and AB in blood samples utilizing M1 bead enrichment has been developed and can be potentially used for the early detection of bacteremia.

Loss to gain: pseudogenes in microorganisms, focusing on eubacteria, and their biological significance.

Pseudogenes are defined as "non-functional" copies of corresponding parent genes. The cognition of pseudogenes continues to be refreshed through accumulating and updating research findings. Previous studies have predominantly focused on mammals, but pseudogenes have received relatively less attention in the field of microbiology. Given the increasing recognition on the importance of pseudogenes, in this review, we focus on several aspects of microorganism pseudogenes, including their classification and characteristics, their generation and fate, their identification, their abundance and distribution, their impact on virulence, their ability to recombine with functional genes, the extent to which some pseudogenes are transcribed and translated, and the relationship between pseudogenes and viruses. By summarizing and organizing the latest research progress, this review will provide a comprehensive perspective and improved understanding on pseudogenes in microorganisms. KEY POINTS: • Concept, classification and characteristics, identification and databases, content, and distribution of microbial pseudogenes are presented. • How pseudogenization contribute to pathogen virulence is highlighted. • Pseudogenes with potential functions in microorganisms are discussed.

Incidence of resistance to ALS and ACCase inhibitors in Echinochloa species and soil microbial composition in Northern Italy.

The increasing amount of weeds surviving herbicide represents a very serious problem for crop management. The interaction between microbial community of soil and herbicide resistance, along with the potential evolutive consequences, are still poorly known and need to be investigated to better understand the impact on agricultural management. In our study, we analyzed the microbial composition of soils in 32 farms, located in the Northern Italy rice-growing area (Lombardy) with the aim to evaluate the relationship between the microbial composition and the incidence of resistance to acetolactate synthase (ALS) and acetyl-CoA carboxylase (ACCase) inhibiting herbicides in Echinochloa species. We observed that the coverage of weeds survived herbicide treatment was higher than 60% in paddy fields with a low microbial biodiversity and less than 5% in those with a high microbial biodiversity. Fungal communities showed a greater reduction in richness than Bacteria. In soils with a reduced microbial diversity, a significant increase of some bacterial and fungal orders (i.e. Lactobacillales, Malasseziales and Diaporthales) was observed. Interestingly, we identified two different microbial profiles linked to the two conditions: high incidence of herbicide resistance (H-HeR) and low incidence of herbicide resistance (L-HeR). Overall, the results we obtained allow us to make hypotheses on the greater or lesser probability of herbicide resistance occurrence based on the composition of the soil microbiome and especially on the degree of biodiversity of the microbial communities.

Characterizing the blood microbiota in healthy and febrile domestic cats via 16s rRNA sequencing.

This study aimed to evaluate the blood bacterial microbiota in healthy and febrile cats. High-quality sequencing reads from the 16S rRNA gene variable region V3-V4 were obtained from genomic blood DNA belonging to 145 healthy cats, and 140 febrile cats. Comparisons between the blood microbiota of healthy and febrile cats revealed dominant presence of Actinobacteria, followed by Firmicutes and Proteobacteria, and a lower relative abundance of Bacteroidetes. Upon lower taxonomic levels, the bacterial composition was significantly different between healthy and febrile cats. The families Faecalibacterium and Kineothrix (Firmicutes), and Phyllobacterium (Proteobacteria) experienced increased abundance in febrile samples. Whereas Thioprofundum (Proteobacteria) demonstrated a significant decrease in abundance in febrile. The bacterial composition and beta diversity within febrile cats was different according to the affected body system (Oral/GI, systemic, skin, and respiratory) at both family and genus levels. Sex and age were not significant factors affecting the blood microbiota of febrile cats nor healthy ones. Age was different between young adult and mature adult healthy cats. Alpha diversity was unaffected by any factors. Overall, the findings suggest that age, health status and nature of disease are significant factors affecting blood microbiota diversity and composition in cats, but sex is not.

Insights into phage-bacteria interaction in cold seep Gigantidas platifrons through metagenomics and transcriptome analyses.

Viruses are crucial for regulating deep-sea microbial communities and biogeochemical cycles. However, their roles are still less characterized in deep-sea holobionts. Bathymodioline mussels are endemic species inhabiting cold seeps and harboring endosymbionts in gill epithelial cells for nutrition. This study unveiled a diverse array of viruses in the gill tissues of Gigantidas platifrons mussels and analyzed the viral metagenome and transcriptome from the gill tissues of Gigantidas platifrons mussels collected from a cold seep in the South Sea. The mussel gills contained various viruses including Baculoviridae, Rountreeviridae, Myoviridae and Siphovirdae, but the active viromes were Myoviridae, Siphoviridae, and Podoviridae belonging to the order Caudovirales. The overall viral community structure showed significant variation among environments with different methane concentrations. Transcriptome analysis indicated high expression of viral structural genes, integrase, and restriction endonuclease genes in a high methane concentration environment, suggesting frequent virus infection and replication. Furthermore, two viruses (GP-phage-contig14 and GP-phage-contig72) interacted with Gigantidas platifrons methanotrophic gill symbionts (bathymodiolin mussels host intracellular methanotrophic Gammaproteobacteria in their gills), showing high expression levels, and have huge different expression in different methane concentrations. Additionally, single-stranded DNA viruses may play a potential auxiliary role in the virus-host interaction using indirect bioinformatics methods. Moreover, the Cro and DNA methylase genes had phylogenetic similarity between the virus and Gigantidas platifrons methanotrophic gill symbionts. This study also explored a variety of viruses in the gill tissues of Gigantidas platifrons and revealed that bacteria interacted with the viruses during the symbiosis with Gigantidas platifrons. This study provides fundamental insights into the interplay of microorganisms within Gigantidas platifrons mussels in deep sea.

Metagenomic evaluation of peanut rhizosphere microbiome from the farms of Saurashtra regions of Gujarat, India.

The narrow zone of soil around the plant roots with maximum microbial activity termed as rhizosphere. Rhizospheric bacteria promote the plant growth directly or indirectly by providing the nutrients and producing antimicrobial compounds. In this study, the rhizospheric microbiota of peanut plants was characterized from different farms using an Illumina-based partial 16S rRNA gene sequencing to evaluate microbial diversity and identify the core microbiome through culture-independent (CI) approach. Further, all rhizospheric bacteria that could grow on various nutrient media were identified, and the diversity of those microbes through culture-dependent method (CD) was then directly compared with their CI counterparts. The microbial population profiles showed a significant correlation with organic carbon and concentration of phosphate, manganese, and potassium in the rhizospheric soil. Genera like Sphingomicrobium, Actinoplanes, Aureimonas _A, Chryseobacterium, members from Sphingomonadaceae, Burkholderiaceae, Pseudomonadaceae, Enterobacteriaceae family, and Bacilli class were found in the core microbiome of peanut plants. As expected, the current study demonstrated more bacterial diversity in the CI method. However, a higher number of sequence variants were exclusively present in the CD approach compared to the number of sequence variants shared between both approaches. These CD-exclusive variants belonged to organisms that are more typically found in soil. Overall, this study portrayed the changes in the rhizospheric microbiota of peanuts in different rhizospheric soil and environmental conditions and gave an idea about core microbiome of peanut plant and comparative bacterial diversity identified through both approaches.

Environmental specificity of karst cave habitats evidenced by diverse symbiotic bacteria in Opiliones.

BACKGROUND: Karst caves serve as natural laboratories, providing organisms with extreme and constant conditions that promote isolation, resulting in a genetic relationship and living environment that is significantly different from those outside the cave. However, research on cave creatures, especially Opiliones, remains scarce, with most studies focused on water, soil, and cave sediments. RESULTS: The structure of symbiotic bacteria in different caves were compared, revealing significant differences. Based on the alpha and beta diversity, symbiotic bacteria abundance and diversity in the cave were similar, but the structure of symbiotic bacteria differed inside and outside the cave. Microorganisms in the cave play an important role in material cycling and energy flow, particularly in the nitrogen cycle. Although microbial diversity varies inside and outside the cave, Opiliones in Beijing caves and Hainan Island exhibited a strong similarity, indicating that the two environments share commonalities. CONCLUSIONS: The karst cave environment possesses high microbial diversity and there are noticeable differences among different caves. Different habitats lead to significant differences in the symbiotic bacteria in Opiliones inside and outside the cave, and cave microorganisms have made efforts to adapt to extreme environments. The similarity in symbiotic bacteria community structure suggests a potential similarity in host environments, providing an explanation for the appearance of Sinonychia martensi in caves in the north.

Arbuscular mycorrhizal fungi and Streptomyces: brothers in arms to shape the structure and function of the hyphosphere microbiome in the early stage of interaction.

BACKGROUND: Fungi and bacteria coexist in a wide variety of environments, and their interactions are now recognized as the norm in most agroecosystems. These microbial communities harbor keystone taxa, which facilitate connectivity between fungal and bacterial communities, influencing their composition and functions. The roots of most plants are associated with arbuscular mycorrhizal (AM) fungi, which develop dense networks of hyphae in the soil. The surface of these hyphae (called the hyphosphere) is the region where multiple interactions with microbial communities can occur, e.g., exchanging or responding to each other's metabolites. However, the presence and importance of keystone taxa in the AM fungal hyphosphere remain largely unknown. RESULTS: Here, we used in vitro and pot cultivation systems of AM fungi to investigate whether certain keystone bacteria were able to shape the microbial communities growing in the hyphosphere and potentially improved the fitness of the AM fungal host. Based on various AM fungi, soil leachates, and synthetic microbial communities, we found that under organic phosphorus (P) conditions, AM fungi could selectively recruit bacteria that enhanced their P nutrition and competed with less P-mobilizing bacteria. Specifically, we observed a privileged interaction between the isolate Streptomyces sp. D1 and AM fungi of the genus Rhizophagus, where (1) the carbon compounds exuded by the fungus were acquired by the bacterium which could mineralize organic P and (2) the in vitro culturable bacterial community residing on the surface of hyphae was in part regulated by Streptomyces sp. D1, primarily by inhibiting the bacteria with weak P-mineralizing ability, thereby enhancing AM fungi to acquire P. CONCLUSIONS: This work highlights the multi-functionality of the keystone bacteria Streptomyces sp. D1 in fungal-bacteria and bacterial-bacterial interactions at the hyphal surface of AM fungi. Video Abstract.

Viruses contribute to microbial diversification in the rumen ecosystem and are associated with certain animal production traits.

BACKGROUND: The rumen microbiome enables ruminants to digest otherwise indigestible feedstuffs, thereby facilitating the production of high-quality protein, albeit with suboptimal efficiency and producing methane. Despite extensive research delineating associations between the rumen microbiome and ruminant production traits, the functional roles of the pervasive and diverse rumen virome remain to be determined. RESULTS: Leveraging a recent comprehensive rumen virome database, this study analyzes virus-microbe linkages, at both species and strain levels, across 551 rumen metagenomes, elucidating patterns of microbial and viral diversity, co-occurrence, and virus-microbe interactions. Additionally, this study assesses the potential role of rumen viruses in microbial diversification by analyzing prophages found in rumen metagenome-assembled genomes. Employing CRISPR-Cas spacer-based matching and virus-microbe co-occurrence network analysis, this study suggests that the viruses in the rumen may regulate microbes at strain and community levels through both antagonistic and mutualistic interactions. Moreover, this study establishes that the rumen virome demonstrates responsiveness to dietary shifts and associations with key animal production traits, including feed efficiency, lactation performance, weight gain, and methane emissions. CONCLUSIONS: These findings provide a substantive framework for further investigations to unravel the functional roles of the virome in the rumen in shaping the microbiome and influencing overall animal production performance. Video Abstract.

ARGNet: using deep neural networks for robust identification and classification of antibiotic resistance genes from sequences.

BACKGROUND: Emergence of antibiotic resistance in bacteria is an important threat to global health. Antibiotic resistance genes (ARGs) are some of the key components to define bacterial resistance and their spread in different environments. Identification of ARGs, particularly from high-throughput sequencing data of the specimens, is the state-of-the-art method for comprehensively monitoring their spread and evolution. Current computational methods to identify ARGs mainly rely on alignment-based sequence similarities with known ARGs. Such approaches are limited by choice of reference databases and may potentially miss novel ARGs. The similarity thresholds are usually simple and could not accommodate variations across different gene families and regions. It is also difficult to scale up when sequence data are increasing. RESULTS: In this study, we developed ARGNet, a deep neural network that incorporates an unsupervised learning autoencoder model to identify ARGs and a multiclass classification convolutional neural network to classify ARGs that do not depend on sequence alignment. This approach enables a more efficient discovery of both known and novel ARGs. ARGNet accepts both amino acid and nucleotide sequences of variable lengths, from partial (30-50 aa; 100-150 nt) sequences to full-length protein or genes, allowing its application in both target sequencing and metagenomic sequencing. Our performance evaluation showed that ARGNet outperformed other deep learning models including DeepARG and HMD-ARG in most of the application scenarios especially quasi-negative test and the analysis of prediction consistency with phylogenetic tree. ARGNet has a reduced inference runtime by up to 57% relative to DeepARG. CONCLUSIONS: ARGNet is flexible, efficient, and accurate at predicting a broad range of ARGs from the sequencing data. ARGNet is freely available at https://github.com/id-bioinfo/ARGNet , with an online service provided at https://ARGNet.hku.hk . Video Abstract.