Microbial Genome Sequences Research Articles

Uncovering Endolysins against Methicillin-Resistant Staphylococcus aureus Using a Microbial Single-Cell Genome Database.

Endolysins, peptidoglycan hydrolases derived from bacteriophages (phages), are being developed as a promising alternative to conventional antibiotics. To obtain highly active endolysins, a diverse library of these endolysins is vital. We propose here microbial single-cell genome sequencing as an efficient tool to discover dozens of previously unknown endolysins, owing to its culture-independent sequencing method. As a proof of concept, we analyzed and recovered endolysin genes within prophage regions of Staphylococcus single-amplified genomes in human skin microbiome samples. We constructed a library of chimeric endolysins by shuffling domains of the natural endolysins and performed high-throughput screening against Staphylococcus aureus. One of the lead endolysins, bbst1027, exhibited desirable antimicrobial properties, such as rapid bactericidal activity, no detectable resistance development, and in vivo efficacy. We foresee that this endolysin discovery pipeline is in principle applicable to any bacterial target and boost the development of novel antimicrobial agents.

Synergic effect of thermo-chemical pretreatment of waste-activated sludge on bio-methane enhancement

Sustainable and environmentally friendly energy production is feasible via anaerobic digestion (AD) of organic wastes, such as waste-activated sludge (WAS). However, due to its limited degradation, a pretreatment strategy is applied to WAS to enhance its bio-degradation and, thus, biogas yield. Alkaline (0.5%–9% g NaOH/gTS, 30 min), microwave (MW) (90°C–175°C), and hybrid (0.5% g NaOH/gTS +125°C) pretreatments were applied to WAS. The characterization of untreated and pretreated WAS revealed that with higher alkaline and MW pretreatment, the soluble chemical oxygen demand (sCOD), carbohydrate, and protein increased; however, the readily biodegradable COD (rbCOD) rate was unlike the sCOD. The sCOD was 7%–18%, 8%–23%, and 37% for alkaline, MW, and hybrid pretreatments, respectively. Stronger alkaline and MW pretreatment induced higher turbidity, capillary suction time, and lower average particle size. AD of alkaline-, MW-, and hybrid-pretreated WAS produced 94% (0.5% NaOH), 125% (MW at 125°C), and 199% (0.5% NaOH and MW at 125°C) increased biogas, respectively, compared to the AD of untreated sludge. The AD data on the alkaline-, MW-, and hybrid-pretreated BMP assays fitted well with the modified Gompertz model with a coefficient of determination above 0.95. The PCA analysis showed that biogas production is closely correlated with pretreatment temperature, VFA production, rbCOD, sCOD, and soluble carbohydrates and protein. Microbial genome sequencing analysis showed an improvement in microbial abundance and diversity. Acetoclastic methanogen (Methanothrix) growth was improved by 37% (MW pretreatment). Abundances of Methanosarcina, using all three metabolic pathways for methanogenesis, were 17, 21, 11, and 48% in the control, alkaline-, MW-, and hybrid-pretreated digestate, respectively, corresponding to 186% improvement in hybrid pretreatment when compared to the control.

Hierarchical determinants in cytotoxic necrotizing factor (CNF) toxins driving Rho G-protein deamidation versus transglutamination.

The cytotoxic necrotizing factor (CNF) family of AB-type bacterial protein toxins catalyze two types of modification on their Rho GTPase substrates: deamidation and transglutamination. It has been established that E. coli CNF1 and its close homolog proteins catalyze primarily deamidation and Bordetella dermonecrotic toxin (DNT) catalyzes primarily transglutamination. The rapidly expanding microbial genome sequencing data have revealed that there are at least 13 full-length variants of CNF1 homologs. CNFx from E. coli strain GN02091 is the most distant from all other members of the CNF family with 50%-55% sequence identity at the protein level and 0.45-0.52 nucleotide substitutions per site at the DNA level. CNFx modifies RhoA, Rac1, and Cdc42, and like CNF1, activates downstream SRE-dependent mitogenic signaling pathways in human HEK293T cells, but at a 1,000-fold higher EC50 value. Unlike other previously characterized CNF toxins, CNFx modifies Rho proteins primarily through transglutamination, as evidenced by gel-shift assay and confirmed by MALDI mass spectral analysis, when coexpressed with Rho-protein substrates in E. coli BL21 cells or through direct treatment of HEK293T cells. A comparison of CNF1 and CNFx sequences identified two critical active-site residues corresponding to positions 832 and 862 in CNF1. Reciprocal site-specific mutations at these residues in each toxin revealed hierarchical rules that define the preference for deamidase versus a transglutaminase activity in CNFs. An additional unique Cys residue at the C-terminus of CNFx was also discovered to be critical for retarding cargo delivery.IMPORTANCECytotoxic necrotizing factor (CNF) toxins not only play important virulence roles in pathogenic E. coli and other bacterial pathogens, but CNF-like genes have also been found in an expanding number of genomes from clinical isolates. Harnessing the power of evolutionary relationships among the CNF toxins enabled the deciphering of the hierarchical active-site determinants that define whether they modify their Rho GTPase substrates through deamidation or transglutamination. With our finding that a distant CNF variant (CNFx) unlike other known CNFs predominantly transglutaminates its Rho GTPase substrates, the paradigm of "CNFs deamidate and DNTs transglutaminate" could finally be attributed to two critical amino acid residues within the active site other than the previously identified catalytic Cys-His dyad residues. The significance of our approach and research findings is that they can be applied to deciphering enzyme reaction determinants and substrate specificities for other bacterial proteins in the development of precision therapeutic strategies.

Periodontal vaccines via plantibodies: Bridging the gap between aspiration and achievement

Periodontitis, a multifaceted immune-inflammatory disorder, is intricately linked to systemic conditions such as cardiovascular disease and diabetes mellitus. Recent advancements in cellular and molecular biology have catalyzed the development of innovative vaccination strategies for various viral diseases. The concept of vaccination, pioneered by Edward Jenner in the late 18th century, capitalizes on the phenomenon of acquired immunity following recovery from an illness. Jenner's groundbreaking work with cowpox virus, which conferred cross-protection against smallpox, laid the foundation for modern vaccination practices.The advent of microbial genome sequencing and bioinformatics has revolutionized our ability to explore the genetic makeup of human pathogens comprehensively. This approach holds promise for identifying novel targets for antimicrobial drugs and vaccines, providing new avenues for combating infectious diseases.Given the pervasive nature of periodontal disease, there is an imperative need for effective management and prevention strategies. In the realm of immunization, the emergence of plant-based vaccines represents a novel paradigm. This review employed various search engines, including PubMed, Embase, Web of Science, Cochrane, Medline, and Google Scholar, to identify pertinent articles in medical and dental research. The findings from these studies underscore the potential efficacy of plant-derived vaccines in addressing a diverse range of disorders, including periodontal disease.This comprehensive review sheds light on the broad spectrum of applications of plant-based vaccines in periodontal care. By harnessing the unique properties of plant-derived antigens, these vaccines hold promise for offering safe, effective, and scalable solutions for the prevention and management of periodontitis. Further research and clinical trials are warranted to explore the full potential of plant-based vaccines in revolutionizing periodontal therapeutics.

Escherichia coli non-coding regulatory regions are highly conserved.

Microbial genome sequences are rapidly accumulating, enabling large-scale studies of sequence variation. Existing studies primarily focus on coding regions to study amino acid substitution patterns in proteins. However, non-coding regulatory regions also play a distinct role in determining physiologic responses. To investigate intergenic sequence variation on a large-scale, we identified non-coding regulatory region alleles across 2350 Escherichia coli strains. This 'alleleome' consists of 117781 unique alleles for 1169 reference regulatory regions (transcribing 1975 genes) at single base-pair resolution. We find that 64% of nucleotide positions are invariant, and variant positions vary in a median of just 0.6% of strains. Additionally, non-coding alleles are sufficient to recover E. coli phylogroups. We find that core promoter elements and transcription factor binding sites are significantly conserved, especially those located upstream of essential or highly-expressed genes. However, variability in conservation of transcription factor binding sites is significant both within and across regulons. Finally, we contrast mutations acquired during adaptive laboratory evolution with wild-type variation, finding that the former preferentially alter positions that the latter conserves. Overall, this analysis elucidates the wealth of information found in E. coli non-coding sequence variation and expands pangenomic studies to non-coding regulatory regions at single-nucleotide resolution.

Bacterial cytochrome P450s: a bioinformatics odyssey of substrate discovery.

Bacterial P450 cytochromes (BacCYPs) are versatile heme-containing proteins responsible for oxidation reactions on a wide range of substrates, contributing to the production of valuable natural products with limitless biotechnological potential. While the sequencing of microbial genomes has provided a wealth of BacCYP sequences, functional characterization lags behind, hindering our understanding of their roles. This study employs a comprehensive approach to predict BacCYP substrate specificity, bridging the gap between sequence and function. We employed an integrated approach combining sequence and functional data analysis, genomic context exploration, 3D structural modeling with molecular docking, and phylogenetic clustering. The research begins with an in-depth analysis of BacCYP sequence diversity and structural characteristics, revealing conserved motifs and recurrent residues in the active site. Phylogenetic analysis identifies distinct groups within the BacCYP family based on sequence similarity. However, our study reveals that sequence alone does not consistently predict substrate specificity, necessitating additional perspectives. The study delves into the genetic context of BacCYPs, utilizing neighboring gene information to infer potential substrates, a method proven very effective in many cases. Molecular docking is employed to assess BacCYP-substrate interactions, confirming potential substrates and providing insights into selectivity. Finally, a comprehensive strategy is proposed for predicting BacCYP substrates, involving all the evaluated approaches. The effectiveness of this strategy is demonstrated with two case studies, highlighting its potential for substrate discovery.

Linking biosynthetic genes to natural products using inverse stable isotopic labeling (InverSIL).

The sequencing of microbial genomes has far outpaced their functional annotation. Stable isotopic labeling can be used to link biosynthetic genes with their natural products; however, the availability of the required isotopically substituted precursors can limit the accessibility of this approach. Here, we describe a method for using inverse stable isotopic labeling (InverSIL) to link biosynthetic genes with their natural products. With InverSIL, a microbe is grown on an isotopically substituted medium to create a fully substituted culture, and subsequently, the incorporation of precursors of natural isotopic abundance can be tracked by mass spectrometry. This eliminates issues with isotopically substituted precursor availability. We demonstrate the utility of this approach by linking a luxI-type acyl-homoserine lactone synthase gene in a bacterium that grows on methanol with its quorum sensing signal products. In the future, InverSIL can also be used to link biosynthetic gene clusters hypothesized to produce siderophores with their natural products.

Resistance gene-guided genome mining reveals the roseopurpurins as inhibitors of cyclin-dependent kinases.

With the significant increase in the availability of microbial genome sequences in recent years, resistance gene-guided genome mining has emerged as a powerful approach for identifying natural products with specific bioactivities. Here, we present the use of this approach to reveal the roseopurpurins as potent inhibitors of cyclin-dependent kinases (CDKs), a class of cell cycle regulators implicated in multiple cancers. We identified a biosynthetic gene cluster (BGC) with a putative resistance gene with homology to human CDK2. Using targeted gene disruption and transcription factor overexpression in Aspergillus uvarum, and heterologous expression of the BGC in Aspergillus nidulans, we demonstrated that roseopurpurin C (1) is produced by this cluster and characterized its biosynthesis. We determined the potency, specificity, and mechanism of action of 1 as well as multiple intermediates and shunt products produced from the BGC. We show that 1 inhibits human CDK2 with a Kiapp of 44 nM, demonstrates selectivity for clinically relevant members of the CDK family, and induces G1 cell cycle arrest in HCT116 cells. Structural analysis of 1 complexed with CDK2 revealed the molecular basis of ATP-competitive inhibition.

PSIII-2 Pediococcus Acidilactici Demonstrates Probiotic Properties and Inhibits the Growth of Enterotoxigenic Escherichia Coli

Abstract Lactic acid bacteria are recognized to possess probiotic properties including modulating host physiology. Probiotics are used as direct-fed microbials in the swine industry to optimize pig performance and production efficiency. In the nursery, probiotics have been shown to mitigate post-weaning diarrhea caused by enterotoxigenic Escherichia coli (ETEC). Studies show beneficial effects of supplementing probiotics and the data were inconsistent. Microbial genome sequencing could help better define the mechanisms of probiotic mode of action and dose required to improve probiotic efficacy. The aim of this study was to determine if Pediococcus acidilactici PECh3A (PA) that has been genome sequenced for determining gut physiology mechanisms expresses probiotic properties in-vitro. The growth curve of PA was conducted to determine colony forming units (CFU)/mL concentrations in 2-hour intervals until plateau at 15 hours. Based on the results of the growth curve dose response analysis were performed for acid and bile tolerance and antimicrobial activity against ETEC (3030-2: K88ac LT and STb). Doses investigated were 1010, 109, and 108 CFU/mL. For the acid and bile tolerance experiment PA was grown to concentration 1010 CFU/mL and was centrifuged and inoculated in De Mab, Rogosa, and Sharpe broth (MRS Broth) at pH 2, 4, or 6.5 (control) or MRS ± 0.3% oxgall (wt/vol), respectively, and incubated for 4 h. Following the 4 h incubation samples were serially diluted, plated, and incubated at 37°C for 24 h to determine percent survival. Antimicrobial inhibition of ETEC was assessed by the agar zone of inhibition (ZOI) methods. PA was grown to previously defined CFU/mL concentrations and 100 µL of the culture and filtered supernatant were plated into wells on nutrient agar plates spread with 107 ETEC CFU/mL. ZOI were measured in mm. Data were analyzed according to a factorial design using PROC MIXED procedures in SAS. Survival in acidic media relative to control media was observed in all doses (108,109, and 1010) at pH 4 and minimally at pH 2 (81.8, 90.6, and 89.5% or 33.8, 28.0, and 0% ±7.7, respectively; P < 0.01). PA survival in 0.3% oxgall increased with increasing dose (74.3, 83.3, and 91.7% ±0.67; P < 0.01). PA culture exhibited antimicrobial activity against ETEC at all doses tested, and the PA filtered supernatant exhibited antimicrobial activity from 109 CFU/mL (4.260 mm ± 0.9437, P < 0.01). Taken together the findings indicate that PA PECh3A exhibits functional probiotic properties to potentially improve swine intestinal physiology. Further in vitro and in vivo experiments will access Pediococcus acidilactici PECh3A function and interaction within the host environment.

MIST: A microbial identification and source tracking system for next-generation sequencing data.

The Professional Committee of Microbiology of the National Pharmacopoeia Commission organized the drafting of the Technical Guidelines for Microbial Whole Genome Sequencing (WGS), aiming to standardize the method process and technical indicators of microbial WGS and ensure the accuracy of sequencing and identification. On the basis of the Guidelines, we developed an integrated microbial identification and source tracking (MIST) system, which could meet the needs of microbial identification and contamination investigation in food and drug quality control. MIST integrates three analysis pipelines: 16S/18S/internal transcribed spacer amplicon-based microbial identification, WGS-based microbial identification, and single-nucleotide polymorphism-based microbial source tracking. MIST can analyze sequence data in a variety of formats, such as Fasta, base call file, and FASTQ. It can be connected to a high-throughput sequencing instrument to acquire sequencing data directly. We also developed a publicly accessible web server for MIST (http://syj.i-sanger.cn).

The microbial biodiversity at the archeological site of Tel Megiddo (Israel).

The ancient city of Tel Megiddo in the Jezreel Valley (Israel), which lasted from the Neolithic to the Iron Age, has been continuously excavated since 1903 and is now recognized as a World Heritage Site. The site features multiple ruins in various areas, including temples and stables, alongside modern constructions, and public access is allowed in designated areas. The site has been studied extensively since the last century; however, its microbiome has never been studied. We carried out the first survey of the microbiomes in Tel Megiddo. Our objectives were to study (i) the unique microbial community structure of the site, (ii) the variation in the microbial communities across areas, (iii) the similarity of the microbiomes to urban and archeological microbes, (iv) the presence and abundance of potential bio-corroding microbes, and (v) the presence and abundance of potentially pathogenic microbes. We collected 40 swab samples from ten major areas and identified microbial taxa using next-generation sequencing of microbial genomes. These genomes were annotated and classified taxonomically and pathogenetically. We found that eight phyla, six of which exist in all ten areas, dominated the site (>99%). The relative sequence abundance of taxa varied between the ruins and the sampled materials and was assessed using all metagenomic reads mapping to a respective taxon. The site hosted unique taxa characteristic of the built environment and exhibited high similarity to the microbiome of other monuments. We identified acid-producing bacteria that may pose a risk to the site through biocorrosion and staining and thus pose a danger to the site's preservation. Differences in the microbiomes of the publicly accessible or inaccessible areas were insignificant; however, pathogens were more abundant in the former. We found that Tel Megiddo combines microbiomes of arid regions and monuments with human pathogens. The findings shed light on the microbial community structures and have relevance for bio-conservation efforts and visitor health.

A bioinformatic workflow for in silico secretome prediction with the lignocellulose degrading ascomycete fungus Parascedosporium putredinis NO1.

The increasing availability of microbial genome sequences provides a reservoir of information for the identification of new microbial enzymes. Genes encoding proteins engaged in extracellular processes are of particular interest as these mediate the interactions microbes have with their environments. However, proteomic analysis of secretomes is challenging and often captures intracellular proteins released through cell death and lysis. Secretome prediction workflows from sequence data are commonly used to filter proteins identified through proteomics but are often simplified to a single step and are not evaluated bioinformatically for their effectiveness. Here, a workflow to predict a fungal secretome was designed and applied to the coding regions of the Parascedosporium putredinis NO1 genome. This ascomycete fungus is an exceptional lignocellulose degrader from which a new lignin-degrading enzyme has previously been identified. The 'secretome isolation' workflow is based on two strategies of localisation prediction and secretion prediction each utilising multiple available tools. The workflow produced three final secretomes with increasing levels of stringency. All three secretomes showed increases in functional annotations for extracellular processes and reductions in annotations for intracellular processes. Multiple sequences isolated as part of the secretome lacked any functional annotation and made exciting candidates for novel enzyme discovery.

Microbial genome (Illumina MiSeq) sequencing of drinking water treatment residuals to evaluate compatibility with environmental applications

The clarification of drinking water leads to the production of large quantities of water treatment residuals (WTRs). DNA was extracted from six WTR samples collected from water treatment plants within the UK to compare their bacterial communities and examine whether factors such as coagulant usage (aluminium versus iron salt), the type of water source (reservoir or river), or leachable chemical composition influence these communities. Bacterial 16S variable region 4 (V4) was amplified and sequenced using Illumina MiSeq sequencing. The most abundant phyla in WTR samples were Proteobacteria, Actinobacteria, Bacteroidetes, Acidobacteria, and Firmicutes, collectively representing 92.77–97.8% of the total bacterial sequences. Statistical analysis of microbial profiles indicated that water source played a significant role in microbial community structure, diversity, and richness, however coagulant type did not. PERMANOVA analysis showed that no single chemical variable (pH, organic matter, or extractable element concentration) influenced microbial composition significantly; however, canonical correspondence analysis of WTR microbiomes yielded a model using all these variables that could be used to explain variations in microbial community structures of WTRs (p < 0.05). No common, potentially toxic cyanobacteria, or related pathogens of concern were found. Analysis with PICRUSt showed that WTRs all had similar predicted microbial functional profiles. Overall, the results indicate that WTRs analysed in this study are unlikely to pose any threat to soil microbial community structure when applied to land as a soil conditioner or enhancer and may help to enhance the soil microbial community.

Targeted Discovery of Cryptic Enediyne Natural Products via FRET-Coupled High-Throughput Elicitor Screening.

Enediyne antibiotics are a striking family of DNA-cleaving natural products with high degrees of cytotoxicity and structural complexity. Microbial genome sequences, which have recently accumulated, point to an untapped trove of "cryptic" enediynes. Most of the cognate biosynthetic gene clusters (BGCs) are sparingly expressed under standard growth conditions, making it difficult to characterize their products. Herein, we report a fluorescence-based DNA cleavage assay coupled with high-throughput elicitor screening for the rapid, targeted discovery of cryptic enediyne metabolites. We applied the approach to Streptomyces clavuligerus, which harbors two such BGCs with unknown products, identified steroids as effective elicitors, and characterized 10 cryptic enediyne-derived natural products, termed clavulynes A-J with unusual carbonate and terminal olefin functionalities, with one of these congeners matching the recently reported jejucarboside. Our results contribute to the growing repertoire of enediynes and provide a blueprint for identifying additional ones in the future.

Trends in forensic microbiology: From classical methods to deep learning.

Forensic microbiology has been widely used in the diagnosis of causes and manner of death, identification of individuals, detection of crime locations, and estimation of postmortem interval. However, the traditional method, microbial culture, has low efficiency, high consumption, and a low degree of quantitative analysis. With the development of high-throughput sequencing technology, advanced bioinformatics, and fast-evolving artificial intelligence, numerous machine learning models, such as RF, SVM, ANN, DNN, regression, PLS, ANOSIM, and ANOVA, have been established with the advancement of the microbiome and metagenomic studies. Recently, deep learning models, including the convolutional neural network (CNN) model and CNN-derived models, improve the accuracy of forensic prognosis using object detection techniques in microorganism image analysis. This review summarizes the application and development of forensic microbiology, as well as the research progress of machine learning (ML) and deep learning (DL) based on microbial genome sequencing and microbial images, and provided a future outlook on forensic microbiology.

Artificial Intelligence in microbiomes analysis: A review of applications in dermatology.

Microorganisms are closely related to skin diseases, and microbiological imbalances or invasions of exogenous pathogens can be a source of various skin diseases. The development and prognosis of such skin diseases are also closely related to the type and composition ratio of microorganisms present. Therefore, through detection of the characteristics and changes in microorganisms, the possibility for diagnosis and prediction of skin diseases can be markedly improved. The abundance of microorganisms and an understanding of the vast amount of biological information associated with these microorganisms has been a formidable task. However, with advances in large-scale sequencing, artificial intelligence (AI)-related machine learning can serve as a means to analyze large-scales of data related to microorganisms along with determinations regarding the type and status of diseases. In this review, we describe some uses of this exciting, new emerging field. In specific, we described the recognition of fungi with convolutional neural networks (CNN), the combined application of microbial genome sequencing and machine learning and applications of AI in the diagnosis of skin diseases as related to the gut-skin axis.

Leveraging comparative genomics to uncover alien genes in bacterial genomes.

A significant challenge in bacterial genomics is to catalogue genes acquired through the evolutionary process of horizontal gene transfer (HGT). Both comparative genomics and sequence composition-based methods have often been invoked to quantify horizontally acquired genes in bacterial genomes. Comparative genomics methods rely on completely sequenced genomes and therefore the confidence in their predictions increases as the databases become more enriched in completely sequenced genomes. Recent developments including in microbial genome sequencing call for reassessment of alien genes based on information-rich resources currently available. We revisited the comparative genomics approach and developed a new algorithm for alien gene detection. Our algorithm compared favourably with the existing comparative genomics-based methods and is capable of detecting both recent and ancient transfers. It can be used as a standalone tool or in concert with other complementary algorithms for comprehensively cataloguing alien genes in bacterial genomes.

Microbial Genome Sequencing and Assembly Using Nanopore Sequencers.

Microbial genomes are typically several million base pairs in length and are relatively easy to sequence and assemble into a single chromosome, given the advances in long-read sequencing platforms such as that of Oxford Nanopore Technologies. This chapter describes the experimental as well as computational steps in the sequencing and assembly of microbial genomes.

Identification and Analysis of the Ankle Microbiome Using Next-Generation DNA Sequencing

Category: Ankle; Basic Sciences/Biologics Introduction/ Purpose: Next-generation DNA sequencing (NGS) technologies have made it possible to detect microbial genome sequences within human tissues with a sensitivity that has not been reached before, allowing research to better characterize “normal” host flora. Researchers have utilized NGS to identify the shoulder microbiome, but there are no reports yet on the ankle microbiome. Using NGS, this study aims to determine whether (1) a unique microbiome exists in human ankle tissues, (2) components of the ankle microbiome impact patient outcomes, and (3) microbes found on the skin make up a normal part of the ankle microbiome within the tissue. Methods: A prospective study recruited 33 patients undergoing total ankle arthroplasty (TAA, n=24) or ankle arthrodesis via an anterior approach (n=9) between November 2020 and October 2021 with one of two fellowship-trained foot and ankle surgeons at an academic medical center. During the operation, the surgeon would swab five layers of the ankle: skin (n=33), retinaculum (n=32), tibialis anterior tendon (n=32), joint capsule (n=32), and distal tibia (n=33). These swabs (N=162) were then sent to MicroGen Diagnostics [Lubbock, TX, USA] for NGS. Retrospective data was also collected from patient records to include demographics, medical comorbidities, surgical indication, postoperative complications, readmission and reoperation rates, and pre- and postoperative patient-reported outcome measures. The majority of subjects underwent surgery for ankle arthritis (97.0%). Most subjects were female (51.5%) and white (93.9%), and mean age at surgery was 60.73 (range, 19-85) years. Mean follow-up duration was 0.75 (range, 0.11-1.29) years. Results: Of the 162 swabs sent for NGS, 19 (11.7%) indicated 27 bacteria were present (positive), while the remaining 143 (88.3%) had no bacteria present (negative). The most common organisms were Cutibacterium acnes (40.7%) and Staphylococcus epidermidis (11.1%). The most bacteria were found in the retinaculum (29.6%), followed by the distal tibia (25.9%) and capsule (22.2%). No PROM nor follow-up duration was associated with the presence of bacteria, or the number of bacteria or affected layers. Similarly, complication (positive=18.2%, negative=22.7%; p=1.000), nonunion (positive=0.0%, negative=28.6%; p=1.000), infection (positive=0.0%, negative=4.5%; p=1.000), 90-day readmission (positive=0.0%, negative=4.5%; p=1.000), and reoperation (positive=0.0%, negative=4.5%; p=1.000) rates did not differ if a subject’s NGS profile was positive or negative. Conclusion: This study found that C. acnes and S. epidermidis were most commonly found in the ankle microbiome, though at a relatively low rate. While there is some evidence to suggest both S. epidermidis and Staphylococcus aureus biofilm formation are identified on explanted ankle prosthetics, no study to date has investigated whether or not these bacteria were present in the ankle joint prior to surgery. Furthermore, there is no evidence that patients presenting with these bacteria at the time of surgery are at a higher risk of failure following TAA or ankle arthrodesis.

MEGAnnotator2: a pipeline for the assembly and annotation of microbial genomes.

The reconstruction of microbial genome sequences by bioinformatic pipelines and the consequent functional annotation of their genes' repertoire are fundamental activities aiming at unveiling their biological mechanisms, such as metabolism, virulence factors, and antimicrobial resistances. Here, we describe the development of the MEGAnnotator2 pipeline able to manage all next-generation sequencing methodologies producing short- and long-read DNA sequences. Starting from raw sequencing data, the updated pipeline can manage multiple analyses leading to the assembly of high-quality genome sequences and the functional classification of their genetic repertoire, providing the user with a useful report constituting features and statistics related to the microbial genome. The updated pipeline is fully automated from the installation to the delivery of the output, thus requiring minimal bioinformatics knowledge to be executed.