Common contaminants in next-generation sequencing that hinder discovery of low-abundance microbes

VenomCap: An exon-capture probe set for the targeted sequencing of snake venom genes

Snake venoms are complex mixtures of toxic proteins that hold significant medical, pharmacological and evolutionary interest. To better understand the genetic diversity underlying snake venoms, we developed VenomCap, a novel exon-capture probe set targeting toxin-coding genes from a wide range of elapid snakes, with a particular focus on the ecologically diverse and medically important subfamily Hydrophiinae. We tested the capture success of VenomCap across 24 species, representing all major elapid lineages. We included snake phylogenomic probes in the VenomCap capture set, allowing us to compare capture performance between venom and phylogenomic loci and to infer elapid phylogenetic relationships. We demonstrated VenomCap's ability to recover exons from ~1500 target markers, representing a total of 24 known venom gene families, which includes the dominant gene families found in elapid venoms. We find that VenomCap's capture results are robust across all elapids sampled, and especially among hydrophiines, with respect to measures of target capture success (target loci matched, sensitivity, specificity and missing data). As a cost-effective and efficient alternative to full genome sequencing, VenomCap can dramatically accelerate the sequencing and analysis of venom gene families. Overall, our tool offers a model for genomic studies on snake venom gene diversity and evolution that can be expanded for comprehensive comparisons across the other families of venomous snakes.

Sequencing RNA from old, dried specimens reveals past viromes and properties of long-surviving RNA

Recovery of virus sequences from old samples provides an opportunity to study virus evolution and reconstruct historic virus-host interactions. Studies of old virus sequences have mainly relied on DNA or on RNA from fixed or frozen samples. The millions of specimens in natural history museums represent a potential treasure trove of old virus sequences, but it is not clear how well RNA survives in old samples. We experimentally assessed the stability of RNA in insects stored dry at room temperature over 72 weeks. Although RNA molecules grew fragmented, RNA yields remained surprisingly constant. RT-qPCR of host and virus RNA showed minimal differences between dried and frozen specimens. To assess RNA survival in much older samples we acquired Drosophila specimens from North American entomological collections. We recovered sequences from known and novel viruses including several coding complete virus genomes from a fly collected in 1908. We found that the virome of D. melanogaster has changed little over the past century. Galbut virus, the most prevalent virus infection in contemporary D. melanogaster, was also the most common in historic samples. Finally, we investigated the genomic and physical features of surviving RNA. RNA that survived was fragmented, chemically damaged, and preferentially double stranded or contained in ribonucleoprotein complexes. This showed that RNA - especially certain types of RNA - can survive in biological specimens over extended periods in the absence of fixation or freezing and confirms the utility of dried specimens to provide a clearer understanding of virus evolution.

Novel phylogenomic inference and 'Out of Asia' biogeography of cobras, coral snakes and their allies

Estimation of evolutionary relationships among lineages that rapidly diversified can be challenging, and, in such instances, inaccurate or unresolved phylogenetic estimates can lead to erroneous conclusions regarding historical geographical ranges of lineages. One example underscoring this issue has been the historical challenge posed by untangling the biogeographic origin of elapoid snakes, which includes numerous dangerously venomous species as well as species not known to be dangerous to humans. The worldwide distribution of this lineage makes it an ideal group for testing hypotheses related to historical faunal exchanges among the many continents and other landmasses occupied by contemporary elapoid species. We developed a novel suite of genomic resources, included worldwide sampling, and inferred a robust estimate of evolutionary relationships, which we leveraged to quantitatively estimate geographical range evolution through the deep-time history of this remarkable radiation. Our phylogenetic and biogeographical estimates of historical ranges definitively reject a lingering former 'Out of Africa' hypothesis and support an 'Out of Asia' scenario involving multiple faunal exchanges between Asia, Africa, Australasia, the Americas and Europe.

Intratumoral microbiome of adenoid cystic carcinomas and comparison with other head and neck cancers

Adenoid cystic carcinoma (ACC) is a rare, usually slow-growing yet aggressive head and neck malignancy. Despite its clinical significance, our understanding of the cellular evolution and microenvironment in ACC remains limited. We investigated the intratumoral microbiomes of 50 ACC tumor tissues and 33 adjacent normal tissues using 16S rRNA gene sequencing. This allowed us to characterize the bacterial communities within the ACC and explore potential associations between the bacterial community structure, patient clinical characteristics, and tumor molecular features obtained through RNA sequencing. The bacterial composition in the ACC was significantly different from that in adjacent normal salivary tissue, and the ACC exhibited diverse levels of species richness. We identified two main microbial subtypes within the ACC: oral-like and gut-like. Oral-like microbiomes, characterized by increased diversity and abundance of Neisseria, Leptotrichia, Actinomyces, Streptococcus, Rothia, and Veillonella (commonly found in healthy oral cavities), were associated with a less aggressive ACC-II molecular subtype and improved patient outcomes. Notably, we identified the same oral genera in oral cancer and head and neck squamous cell carcinomas. In both cancers, they were part of shared oral communities associated with a more diverse microbiome, less aggressive tumor phenotype, and better survival that reveal the genera as potential pancancer biomarkers for favorable microbiomes in ACC and other head and neck cancers. Conversely, gut-like intratumoral microbiomes, which feature low diversity and colonization by gut mucus layer-degrading species, such as Bacteroides, Akkermansia, Blautia, Bifidobacterium, and Enterococcus, were associated with poorer outcomes. Elevated levels of Bacteroides thetaiotaomicron were independently associated with significantly worse survival and positively correlated with tumor cell biosynthesis of glycan-based cell membrane components.

Detection of colorectal-cancer-associated bacterial taxa in fecal samples using next-generation sequencing and 19 newly established qPCR assays

We have previously identified increased levels of distinct bacterial taxa within mucosal biopsies from colorectal cancer (CRC) patients. Following prior research, the aim of this study was to investigate the detection of the same CRC-associated bacteria in fecal samples and to evaluate the suitability of fecal samples as a non-invasive material for the detection of CRC-associated bacteria. Next-generation sequencing (NGS) of the 16S ribosomal RNA (rRNA) V4 region was performed to evaluate the detection of the CRC-associated bacteria in the fecal microbiota of cancer patients, patients with adenomatous polyp and healthy controls. Furthermore, 19 novel species-specific quantitative PCR (qPCR) assays were established to detect the CRC-associated bacteria. Approximately, 75% of the bacterial taxa identified in biopsies were reflected in fecal samples. NGS failed to detect low-abundance CRC-associated taxa in fecal samples, whereas qPCR exhibited high sensitivity and specificity in identifying all targeted taxa. Comparison of fecal microbial composition between the different patient groups showed enrichment of Fusobacterium nucleatum, Parvimonas micra, and Gemella morbillorum in cancer patients. Our findings suggest that low-abundance mucosa-associated bacteria can be detected in fecal samples using sensitive qPCR assays.

Integrative analysis of systemic lupus erythematosus biomarkers: Role of fecal hsa-mir-223-3p and gut microbiota in transkingdom dynamics

Systemic lupus erythematosus (SLE) involves a florid set of clinical manifestations whose autoreactive origin is characterized by an overactivation of the immune system and the production of a large number of autoantibodies. Because it is a complex pathology with an inflammatory component, its pathogenesis is not yet fully understood, assuming both genetic and environmental predisposing factors. Currently, it is known that the role of the human microbiome is crucial in maintaining the transkingdom balance between commensal microorganisms and the immune system. In the present work we study the intestinal microbiota of Argentine patients with different stages of SLE receiving or not different treatments. Microbiota composition and fecal miRNAs were assessed by 16 S sequencing and qPCR. hsa-miR-223-3p, a miRNA involved in several inflammation regulation pathways, was found underexpressed in SLE patients without immunosuppressive treatment. In terms of microbiota there were clear differences in population structure (Weighted and Unweighted Unifrac distances, p-value <0.05) and core microbiome between cases and controls. In addition, Collinsella, Bifidobacterium, Streptococcus genera and aromatics degradation metabolisms were overrepresented in the SLE group. Medical treatment was also determinant as several microbial metabolic pathways were influenced by immunosuppressive therapy. Particularly, allantoin degradation metabolism was differentially expressed in the group of patients receiving immunosuppressants. Finally, we performed a logistic regression model (LASSO: least absolute shrinkage and selection operator) considering the expression levels of the fecal hsa-miR223-3p; the core microbiota; the differentially abundant bacterial taxa and the differentially abundant metabolic pathways (p<0.05). The model predicted that SLE patients could be associated with greater relative abundance of the formaldehyde oxidation pathway (RUMP_PWY). On the contrary, the preponderance of the ketodeoxyoctonate (Kdo) biosynthesis and activation route (PWY_1269) and the genera Lachnospiraceae_UCG_004, Lachnospira, Victivallis and UCG_003 (genus belonging to the family Oscillospiraceae of the class Clostridia) were associated with a control phenotype. Overall, the present work could contribute to the development of integral diagnostic tools for the comprehensive phenotyping of patients with SLE. In this sense, studying the commensal microbial profile and possible pathobionts associated with SLE in our population proposes more effective and precise strategies to explore possible treatments based on the microbiota of SLE patients.

Comprehensive Assessment of the Intrinsic Pancreatic Microbiome

OBJECTIVE

We sought to comprehensively profile tissue and cyst fluid in patients with benign, precancerous, and cancerous conditions of the pancreas to characterize the intrinsic pancreatic microbiome.

SUMMARY BACKGROUND DATA

Small studies in pancreatic ductal adenocarcinoma (PDAC) and intraductal papillary mucinous neoplasm (IPMN) have suggested that intra-pancreatic microbial dysbiosis may drive malignant transformation.

METHODS

Pancreatic samples were collected at the time of resection from 109 patients. Samples included tumor tissue (control, n=20; IPMN, n=20; PDAC, n=19) and pancreatic cyst fluid (IPMN, n=30; SCA, n=10; MCN, n=10). Assessment of bacterial DNA by quantitative PCR and 16S ribosomal RNA gene sequencing was performed. Downstream analyses determined the relative abundances of individual taxa between groups and compared intergroup diversity. Whole-genome sequencing data from 140 patients with PDAC in the National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium (CPTAC) were analyzed to validate findings.

RESULTS

Sequencing of pancreatic tissue yielded few microbial reads regardless of diagnosis, and analysis of pancreatic tissue showed no difference in the abundance and composition of bacterial taxa between normal pancreas, IPMN, or PDAC groups. Low-grade dysplasia (LGD) and high-grade dysplasia (HGD) IPMN were characterized by low bacterial abundances with no difference in tissue composition and a slight increase in Pseudomonas and Sediminibacterium in HGD cyst fluid. Decontamination analysis using the CPTAC database confirmed a low-biomass, low-diversity intrinsic pancreatic microbiome that did not differ by pathology.

CONCLUSIONS

Our analysis of the pancreatic microbiome demonstrated very low intrinsic biomass that is relatively conserved across diverse neoplastic conditions and thus unlikely to drive malignant transformation.

Preanalytical Challenges of Molecular Microbiology Tests

As infectious disease diagnostics increasingly incorporates molecular techniques, there are unique preanalytical concerns that must be considered. First, noninvasive specimen types that may be inadequate for culture-based diagnostics may be acceptable when using molecular tests. Second, specimen containers must be evaluated for the presence of substances that may interfere with amplification or sequencing reactions. Finally, the capacity of transport, storage, and processing conditions to maintain nucleic acid integrity and avoid contamination must be assessed. This review explores these issues and the effects they may have on result quality.

Application of VirCapSeq-VERT and BacCapSeq in the diagnosis of presumed and definitive neuroinfectious diseases

Unbiased high-throughput sequencing (HTS) has enabled new insights into the diversity of agents implicated in central nervous system (CNS) infections. The addition of positive selection capture methods to HTS has enhanced the sensitivity while reducing sequencing costs and the complexity of bioinformatic analysis. Here we report the use of virus capture-based sequencing for vertebrate viruses (VirCapSeq-VERT) and bacterial capture sequencing (BacCapSeq) in investigating CNS infections. Thirty-four samples were categorized: (1) patients with definitive CNS infection by routine testing; (2) patients meeting clinically the Brighton criteria (BC) for meningoencephalitis; (3) patients with presumptive infectious etiology highest on the differential. RNA extracts from cerebrospinal fluid (CSF) were used for VirCapSeq-VERT, and DNA extracts were used for BacCapSeq analysis. Among 8 samples from known CNS infections in group 1, VirCapSeq and BacCapSeq confirmed 3 expected diagnoses (42.8%), were negative in 2 (25%), yielded an alternative result in 1 (11.1%), and did not detect 2 expected negative pathogens. The confirmed cases identified HHV-6, HSV-2, and VZV while the negative samples included JCV and HSV-2. In groups 2 and 3, 11/26 samples (42%) were positive for at least one pathogen; however, 27% of the total samples (7/26) were positive for commensal organisms. No microbial nucleic acids were detected in negative control samples. HTS showed limited promise for pathogen identification in presumed CNS infectious diseases in our small sample. Before conducting larger-scale prospective studies to assess the clinical value of this novel technique, clinicians should understand the benefits and limitations of using this modality.

Benchmarking MicrobIEM - a user-friendly tool for decontamination of microbiome sequencing data

BACKGROUND

Microbiome analysis is becoming a standard component in many scientific studies, but also requires extensive quality control of the 16S rRNA gene sequencing data prior to analysis. In particular, when investigating low-biomass microbial environments such as human skin, contaminants distort the true microbiome sample composition and need to be removed bioinformatically. We introduce MicrobIEM, a novel tool to bioinformatically remove contaminants using negative controls.

RESULTS

We benchmarked MicrobIEM against five established decontamination approaches in four 16S rRNA amplicon sequencing datasets: three serially diluted mock communities (108-103 cells, 0.4-80% contamination) with even or staggered taxon compositions and a skin microbiome dataset. Results depended strongly on user-selected algorithm parameters. Overall, sample-based algorithms separated mock and contaminant sequences best in the even mock, whereas control-based algorithms performed better in the two staggered mocks, particularly in low-biomass samples (≤ 106 cells). We show that a correct decontamination benchmarking requires realistic staggered mock communities and unbiased evaluation measures such as Youden's index. In the skin dataset, the Decontam prevalence filter and MicrobIEM's ratio filter effectively reduced common contaminants while keeping skin-associated genera.

CONCLUSIONS

MicrobIEM's ratio filter for decontamination performs better or as good as established bioinformatic decontamination tools. In contrast to established tools, MicrobIEM additionally provides interactive plots and supports selecting appropriate filtering parameters via a user-friendly graphical user interface. Therefore, MicrobIEM is the first quality control tool for microbiome experts without coding experience.

Bacterial and fungal characterization of pancreatic adenocarcinoma from Endoscopic Ultrasound-guided biopsies

Introduction

The tumor microbiome (TM) has been linked to pancreatic cancer prognosis. Specific microbes can confer tumor resistance to therapies. Early knowledge of the TM at time of diagnosis would be clinically relevant for precision therapy based on microbial composition. However, it is difficult to define the TM prior to surgical resection.

Methods

In this pilot feasibility study, patients underwent Endoscopic Ultrasound-Fine Needle Aspiration (EUS-FNA) biopsy of pancreatic adenocarcinoma. These samples were analyzed using 16S rRNA and internal transcribed spacer (ITS) sequencing for characterization of the tumor bacteria and fungi.

Result

After in silico decontamination and comparison to non-matched tumor, we were able to characterize the TM in biopsies, which was comparable to the TM from surgical specimens.

Discussion

EUS-FNA biopsy may represent a feasible modality to characterize the pancreatic TM prior to surgical resection with proper decontamination strategies and improvements in matched controls.

The visceral adipose tissue bacterial microbiota provides a signature of obesity based on inferred metagenomic functions

BACKGROUND

Metabolic inflammation mediated obesity requires bacterial molecules to trigger immune and adipose cells leading to inflammation and adipose depot development. In addition to the well-established gut microbiota dysbiosis, a leaky gut has been identified in patients with obesity and animal models, characterized by the presence of a tissue microbiota in the adipose fat pads.

METHODS

To determine its potential role, we sequenced the bacterial 16 S rRNA genes in the visceral adipose depot of patients with obesity. Taking great care (surgical, biochemical, and bioinformatic) to avoid environmental contaminants. We performed statistical discriminant analyses to identify specific signatures and constructed network of interactions between variables.

RESULTS

The data showed that a specific 16SrRNA gene signature was composed of numerous bacterial families discriminating between lean versus patients with obesity and people with severe obesity. The main discriminant families were Burkholderiaceae, Yearsiniaceae, and Xanthomonadaceae, all of which were gram-negative. Interestingly, the Morganellaceae were totally absent from people without obesity while preponderant in all in patients with obesity. To generate hypotheses regarding their potential role, we inferred metabolic pathways from the 16SrRNA gene signatures. We identified several pathways associated with adenosyl-cobalamine previously described to be linked with adipose tissue development. We further identified chorismate biosynthesis, which is involved in aromatic amino-acid metabolism and could play a role in fat pad development. This innovative approach generates novel hypotheses regarding the gut to adipose tissue axis.

CONCLUSIONS

This innovative approach generates novel hypotheses regarding the gut to adipose tissue axis in obesity and notably the potential role of tissue microbiota.

DNA sequencing at the picogram level to investigate life on Mars and Earth

DNA is an incontrovertible biosignature whose sequencing aids in species identification, genome functionality, and evolutionary relationships. To study life within the rocks of Earth and Mars, we demonstrate, in an ISO5 clean room, a procedure based on nanopore technology that correctly identifies organisms at picogram levels of DNA without amplification. Our study with E. coli and S. cerevisiae DNA samples showed that MinION sequencer (Oxford Nanopore Technologies) can unequivocally detect and characterise microbes with as little as 2 pg of input with just 50 active nanopores. This result is an excellent advancement in sensitivity, immediately applicable to investigating low biomass samples. This value is also at the level of possible background contamination associated with the reagents and the environment. Cultivation of natural and heat-treated Martian analogue (MMS-2) regolith samples, exposed to atmospheric water vapour or in increasing water concentrations, led to the extraction of 600-1000 pg of DNA from 500 mg of soil. Applying the low detectability technology enabled through MinION sequencer for a natural low biomass setting, we characterised the dry MMS-2 and found few soil-related organisms and airborne contaminants. The picogram detection level and the procedure presented here, may be of interest for the future Mars sample Return program, and the life research and planetary protection studies that will be implemented through the sample safety assessment.

Challenges and insights in the exploration of the low abundance human ocular surface microbiome

Purpose

The low microbial abundance on the ocular surface results in challenges in the characterization of its microbiome. The purpose of this study was to reveal factors introducing bias in the pipeline from sample collection to data analysis of low-abundant microbiomes.

Methods

Lower conjunctiva and lower lid swabs were collected from six participants using either standard cotton or flocked nylon swabs. Microbial DNA was isolated with two different kits (with or without prior host DNA depletion and mechanical lysis), followed by whole-metagenome shotgun sequencing with a high sequencing depth set at 60 million reads per sample. The relative microbial compositions were generated using the two different tools MetaPhlan3 and Kraken2.

Results

The total amount of extracted DNA was increased by using nylon flocked swabs on the lower conjunctiva. In total, 269 microbial species were detected. The most abundant bacterial phyla were Actinobacteria, Firmicutes and Proteobacteria. Depending on the DNA extraction kit and tool used for profiling, the microbial composition and the relative abundance of viruses varied.

Conclusion

The microbial composition on the ocular surface is not dependent on the swab type, but on the DNA extraction method and profiling tool. These factors have to be considered in further studies about the ocular surface microbiome and other sparsely colonized microbiomes in order to improve data reproducibility. Understanding challenges and biases in the characterization of the ocular surface microbiome may set the basis for microbiome-altering interventions for treatment of ocular surface associated diseases.

Uterine Microbiome: Does the Sampling Technique Matter?

Studies have proven the significance of microbial communities in various parts of the human body for health. In recent years it has been discovered that the uterine cavity is not sterile, and endometrium has its own microbiome which appears to have an impact on female fertility and gynecological pathologies. Lactobacillus has shown to dominate the microbial profile in the uterus and is considered an indicator of a healthy uterine environment. Yet, many argue that the Lactobacillus dominance is due to vaginal contamination during the sampling process. To date there is no clearly defined healthy endometrial microbial profile, which is largely due to the fact that determining the microbial community from the endometrium is complicated, and there is currently no consensus on sampling methods for the endometrial microbiome. As a result, this restricts ability to replicate discoveries made in other cohorts. Here we aim to give an overview of the sampling methods used and discuss what impedes the endometrial microbiome studies as well as how to reach a consensus on the study design. This knowledge could be incorporated into the future research and the knowledge on endometrial microbiome could be included into the diagnostics and treatment of female reproductive health.

Presence of p25alpha-Domain in Seed Plants (Spermatophyta): Microbial/Animal Contaminations and/or Orthologs

Genome and transcriptome assembly data often contain DNA and RNA contaminations from external organisms, introduced during nucleotide extraction or sequencing. In this study, contamination of seed plant (Spermatophyta) transcriptomes/genomes with p25alpha domain encoding RNA/DNA was systematically investigated. This domain only occurs in organisms possessing a eukaryotic flagellum (cilium), which seed plants usually do not have. Nucleotide sequences available at the National Center for Biotechnology Information website, including transcriptome shotgun assemblies (TSAs), whole-genome shotgun contigs (WGSs), and expressed sequence tags (ESTs), were searched for sequences containing a p25alpha domain in Spermatophyta. Despite the lack of proteins containing the p25alpha domain, such fragments or complete mRNAs in some EST and TSA databases were found. A phylogenetic analysis showed that these were contaminations whose possible sources were microorganisms (flagellated fungi, protists) and arthropods/worms; however, there were cases where it cannot be excluded that the sequences found were genuine hits and not of external origin.

Application of VirCapSeq-VERT and BacCapSeq In the Diagnosis of Presumed and Definitive Neuroinfectious Diseases

Background

Unbiased high-throughput sequencing (HTS) has enabled new insights into the diversity of agents implicated in central nervous system (CNS) infections. The addition of positive selection capture methods to HTS has enhanced the sensitivity while reducing sequencing costs and complexity of bioinformatic analysis. Here we report the use of virus capture based sequencing for vertebrate viruses (VirCapSeq-VERT) and bacterial capture sequencing (BacCapSeq) in investigating CNS infections.

Design/Methods

Thirty-four samples were categorized: (1) Patients with definitive CNS infection by routine testing; (2) Patients meeting clinically Brighton Criteria (BC) for meningoencephalitis (3) Patients with presumptive infectious etiology highest on the differential. RNA extracts from cerebrospinal fluid (CSF) were used for VirCapSeq-VERT and DNA extracts were used for BacCapSeq analysis.

Results

Among 8 samples from known CNS infections in group 1, VirCapSeq and BacCapSeq confirmed 3 expected diagnoses (42.8%), were negative in 2 (25%), yielded an alternative result in 1 (11.1%), and did not detect 2 expected negative pathogens. The confirmed cases identified HHV-6, HSV-2, and VZV while the negative samples included JCV and HSV-2. In groups 2 and 3,11/26 samples (42%) were positive for at least one pathogen, however 27% of the total samples (7/26) were positive for commensal organisms. No microbial nucleic acids were detected in negative control samples.

Conclusions

HTS showed limited promise for pathogen identification in presumed CNS infectious diseases in our small sample. Before conducting larger-scale prospective studies to assess clinical value of this novel technique, clinicians should understand benefits and limitations of using this modality.

Carryover Contamination-Controlled Amplicon Sequencing Workflow for Accurate Qualitative and Quantitative Detection of Pathogens: a Case Study on SARS-CoV-2

Carryover contamination during amplicon sequencing workflow (AMP-Seq) put the accuracy of the high-throughput detection for pathogens at risk. The purpose of this study is to develop a carryover contaminations-controlled AMP-Seq (ccAMP-Seq) workflow to enable accurate qualitative and quantitative detection for pathogens. By using the AMP-Seq workflow to detect SARS-CoV-2, Aerosols, reagents and pipettes were identified as potential sources of contaminations and ccAMP-Seq was then developed. ccAMP-Seq used filter tips and physically isolation of experimental steps to avoid cross contamination, synthetic DNA spike-ins to compete with contaminations and quantify SARS-CoV-2, dUTP/uracil DNA glycosylase system to digest the carryover contaminations, and a new data analysis procedure to remove the sequencing reads from contaminations. Compared to AMP-Seq, the contamination level of ccAMP-Seq was at least 22-folds lower and the detection limit was also about an order of magnitude lower-as low as one copy/reaction. By testing the dilution series of SARS-CoV-2 nucleic acid standard, ccAMP-Seq showed 100% sensitivity and specificity. The high sensitivity of ccAMP-Seq was further confirmed by the detection of SARS-CoV-2 from 62 clinical samples. The consistency between qPCR and ccAMP-Seq was 100% for all the 53 qPCR-positive clinical samples. Seven qPCR-negative clinical samples were found to be positive by ccAMP-Seq, which was confirmed by extra qPCR tests on subsequent samples from the same patients. This study presents a carryover contamination-controlled, accurate qualitative and quantitative amplicon sequencing workflow that addresses the critical problem of pathogen detection for infectious diseases. IMPORTANCE Accuracy, a key indicator of pathogen detection technology, is compromised by carryover contamination in the amplicon sequencing workflow. Taking the detection of SARS-CoV-2 as case, this study presents a new carryover contamination-controlled amplicon sequencing workflow. The new workflow significantly reduces the degree of contamination in the workflow, thereby significantly improving the accuracy and sensitivity of the SARS-CoV-2 detection and empowering the ability of quantitative detection. More importantly, the use of the new workflow is simple and economical. Therefore, the results of this study can be easily applied to other microorganism, which has great significance for improving the detection level of microorganism.

The Interplay between Microbiota and Chemotherapy-Derived Metabolites in Breast Cancer

The most common cancer in women is breast cancer, which is also the second leading cause of death in this group. It is, however, important to note that some women will develop or will not develop breast cancer regardless of whether certain known risk factors are present. On the other hand, certain compounds are produced by bacteria in the gut, such as short-chain fatty acids, secondary bile acids, and other metabolites that may be linked to breast cancer development and mediate the chemotherapy response. Modeling the microbiota through dietary intervention and identifying metabolites directly associated with breast cancer and its complications may be useful to identify actionable targets and improve the effect of antiangiogenic therapies. Metabolomics is therefore a complementary approach to metagenomics for this purpose. As a result of the combination of both techniques, a better understanding of molecular biology and oncogenesis can be obtained. This article reviews recent literature about the influence of bacterial metabolites and chemotherapy metabolites in breast cancer patients, as well as the influence of diet.

Recovery of metagenomic data from the Aedes aegypti microbiome using a reproducible snakemake pipeline: MINUUR

Background: Ongoing research of the mosquito microbiome aims to uncover novel strategies to reduce pathogen transmission. Sequencing costs, especially for metagenomics, are however still significant. A resource that is increasingly used to gain insights into host-associated microbiomes is the large amount of publicly available genomic data based on whole organisms like mosquitoes, which includes sequencing reads of the host-associated microbes and provides the opportunity to gain additional value from these initially host-focused sequencing projects. Methods: To analyse non-host reads from existing genomic data, we developed a snakemake workflow called MINUUR (Microbial INsights Using Unmapped Reads). Within MINUUR, reads derived from the host-associated microbiome were extracted and characterised using taxonomic classifications and metagenome assembly followed by binning and quality assessment. We applied this pipeline to five publicly available Aedes aegypti genomic datasets, consisting of 62 samples with a broad range of sequencing depths. Results: We demonstrate that MINUUR recovers previously identified phyla and genera and is able to extract bacterial metagenome assembled genomes (MAGs) associated to the microbiome. Of these MAGS, 42 are high-quality representatives with >90% completeness and <5% contamination. These MAGs improve the genomic representation of the mosquito microbiome and can be used to facilitate genomic investigation of key genes of interest. Furthermore, we show that samples with a high number of KRAKEN2 assigned reads produce more MAGs. Conclusions: Our metagenomics workflow, MINUUR, was applied to a range of Aedes aegypti genomic samples to characterise microbiome-associated reads. We confirm the presence of key mosquito-associated symbionts that have previously been identified in other studies and recovered high-quality bacterial MAGs. In addition, MINUUR and its associated documentation are freely available on GitHub and provide researchers with a convenient workflow to investigate microbiome data included in the sequencing data for any applicable host genome of interest.

Human Knee Has A Distinct Microbiome: Implications for Periprosthetic Joint Infection

INTRODUCTION

Pathogens causing prosthetic joint infection are thought to gain access to the knee during surgery or from a remote site in the body. Recent studies have shown that there is a distinct microbiome in various sites of the body. This prospective study, and first of its kind, was set up to investigate the presence of possible microbiome in human knee and compare the profile in different knee conditions.

METHODS

This transversal study prospectively obtained synovial fluid from 65 knees (55 patients) with various conditions that included normal knee, osteoarthritis, aseptic revision, and those undergoing revision for periprosthetic joint infection (PJI). The contralateral knee of patients who had a PJI were also aspirated to compare the composition of the PJI knee with uninfected contralateral knee. A minimum of 3 milliliters (ml) of synovial fluid was collected per joint. Then, the samples were aliquoted for culture and next generation sequencing (NGS) analysis.

RESULTS

The highest number of species was found in native osteoarthritic knees (P≤0.035). Cutibacterium, Staphylococcus, and Paracoccus species were dominant in native non-osteoarthritic knees, and meanwhile a markedly high abundance of Proteobacteria was observed in the osteoarthritic joints. Moreover, the contralateral and aseptic revision knees showed a similar trend in bacterial composition (P=0.75). The NGS analysis of patients who had PJI diagnosis, confirmed the culture results.

DISCUSSION/CONCLUSION

Distinct knee microbiome profiles can be detected in patients who have osteoarthritis and other knee conditions. The distinct microbiome in the knee joint and the close host-microbe relationships within the knee joint may play a decisive role in the development of osteoarthritis and periprosthetic joint infection.

Using strain-resolved analysis to identify contamination in metagenomics data

BACKGROUND

Metagenomics analyses can be negatively impacted by DNA contamination. While external sources of contamination such as DNA extraction kits have been widely reported and investigated, contamination originating within the study itself remains underreported.

RESULTS

Here, we applied high-resolution strain-resolved analyses to identify contamination in two large-scale clinical metagenomics datasets. By mapping strain sharing to DNA extraction plates, we identified well-to-well contamination in both negative controls and biological samples in one dataset. Such contamination is more likely to occur among samples that are on the same or adjacent columns or rows of the extraction plate than samples that are far apart. Our strain-resolved workflow also reveals the presence of externally derived contamination, primarily in the other dataset. Overall, in both datasets, contamination is more significant in samples with lower biomass.

CONCLUSION

Our work demonstrates that genome-resolved strain tracking, with its essentially genome-wide nucleotide-level resolution, can be used to detect contamination in sequencing-based microbiome studies. Our results underscore the value of strain-specific methods to detect contamination and the critical importance of looking for contamination beyond negative and positive controls. Video Abstract.

Gallbladder microbiota in healthy dogs and dogs with mucocele formation

To date studies have not investigated the culture-independent microbiome of bile from dogs, a species where aseptic collection of bile under ultrasound guidance is somewhat routine. Despite frequent collection of bile for culture-based diagnosis of bacterial cholecystitis, it is unknown whether bile from healthy dogs harbors uncultivable bacteria or a core microbiota. The answer to this question is critical to understanding the pathogenesis of biliary infection and as a baseline to exploration of other biliary diseases in dogs where uncultivable bacteria could play a pathogenic role. A pressing example of such a disease would be gallbladder mucocele formation in dogs. This prevalent and deadly condition is characterized by excessive secretion of abnormal mucus by the gallbladder epithelium that can eventually lead to rupture of the gallbladder or obstruction of bile flow. The cause of mucocele formation is unknown as is whether uncultivable, and therefore unrecognized, bacteria play any systematic role in pathogenesis. In this study we applied next-generation 16S rRNA gene sequencing to identify the culture-negative bacterial community of gallbladder bile from healthy dogs and gallbladder mucus from dogs with mucocele formation. Integral to our study was the use of 2 separate DNA isolations on each sample using different extraction methods and sequencing of negative control samples enabling recognition and curation of contaminating sequences. Microbiota findings were validated by simultaneous culture-based identification, cytological examination of bile, and fluorescence in-situ hybridization (FISH) performed on gallbladder mucosa. Using culture-dependent, cytological, FISH, and 16S rRNA sequencing approaches, results of our study do not support existence of a core microbiome in the bile of healthy dogs or gallbladder mucus from dogs with mucocele formation. Our findings further document how contaminating sequences can significantly contribute to the results of sequencing analysis when performed on samples with low bacterial biomass.

Questioning the fetal microbiome illustrates pitfalls of low-biomass microbial studies

Whether the human fetus and the prenatal intrauterine environment (amniotic fluid and placenta) are stably colonized by microbial communities in a healthy pregnancy remains a subject of debate. Here we evaluate recent studies that characterized microbial populations in human fetuses from the perspectives of reproductive biology, microbial ecology, bioinformatics, immunology, clinical microbiology and gnotobiology, and assess possible mechanisms by which the fetus might interact with microorganisms. Our analysis indicates that the detected microbial signals are likely the result of contamination during the clinical procedures to obtain fetal samples or during DNA extraction and DNA sequencing. Furthermore, the existence of live and replicating microbial populations in healthy fetal tissues is not compatible with fundamental concepts of immunology, clinical microbiology and the derivation of germ-free mammals. These conclusions are important to our understanding of human immune development and illustrate common pitfalls in the microbial analyses of many other low-biomass environments. The pursuit of a fetal microbiome serves as a cautionary example of the challenges of sequence-based microbiome studies when biomass is low or absent, and emphasizes the need for a trans-disciplinary approach that goes beyond contamination controls by also incorporating biological, ecological and mechanistic concepts.

Contamination detection and microbiome exploration with GRIMER

BACKGROUND

Contamination detection is a important step that should be carefully considered in early stages when designing and performing microbiome studies to avoid biased outcomes. Detecting and removing true contaminants is challenging, especially in low-biomass samples or in studies lacking proper controls. Interactive visualizations and analysis platforms are crucial to better guide this step, to help to identify and detect noisy patterns that could potentially be contamination. Additionally, external evidence, like aggregation of several contamination detection methods and the use of common contaminants reported in the literature, could help to discover and mitigate contamination.

RESULTS

We propose GRIMER, a tool that performs automated analyses and generates a portable and interactive dashboard integrating annotation, taxonomy, and metadata. It unifies several sources of evidence to help detect contamination. GRIMER is independent of quantification methods and directly analyzes contingency tables to create an interactive and offline report. Reports can be created in seconds and are accessible for nonspecialists, providing an intuitive set of charts to explore data distribution among observations and samples and its connections with external sources. Further, we compiled and used an extensive list of possible external contaminant taxa and common contaminants with 210 genera and 627 species reported in 22 published articles.

CONCLUSION

GRIMER enables visual data exploration and analysis, supporting contamination detection in microbiome studies. The tool and data presented are open source and available at https://gitlab.com/dacs-hpi/grimer.

Meta-analysis of sputum microbiome studies identifies airway disease-specific taxonomic and functional signatures

Introduction. Studying taxonomic and functional signatures of respiratory microbiomes provide a better understanding of airway diseases.Gap Statement. Several human airway metagenomics studies have identified taxonomic and functional features restricted to a single disease condition and the findings are not comparable across airway diseases due to use of different samples, NGS platforms, and bioinformatics databases and tools.Aim. To study the microbial taxonomic and functional components of sputum microbiome across airway diseases and healthy smokers.Methodology. Here, 57 whole metagenome shotgun sequencing (WMSS) runs coming from the sputum of five airway diseases: asthma, bronchiectasis, chronic obstructive pulmonary diseases (COPD), cystic fibrosis (CF), tuberculosis (TB), and healthy smokers as the control were reanalysed using a common WMSS analysis pipeline.Results. Shannon's index (alpha diversity) of the healthy smoker group was the highest among all. The beta diversity showed that the sputum microbiome is distinct in major airway diseases such as asthma, COPD and cystic fibrosis. The microbial composition based on differential analysis showed that there are specific markers for each airway disease like Acinetobacter bereziniae as a marker for COPD and Achromobacter xylosoxidans as a marker of cystic fibrosis. Pathways and metabolites identified from the sputum microbiome of these five diseases and healthy smokers also show specific markers. 'ppGpp biosynthesis' and 'purine ribonucleosides degradation' pathways were identified as differential markers for bronchiectasis and COPD. In this meta-analysis, besides bacteria kingdom, Aspergillus fumigatus was detected in asthma and COPD, and Roseolovirus human betaherpesvirus 7 was detected in COPD. Our analysis showed that the majority of the gene families specific to the drug-resistant associated genes were detected from opportunistic pathogens across all the groups.Conclusion. In summary, the specific species in the sputum of airway diseases along with the microbial features like specific gene families, pathways, and metabolites were identified which can be explored for better diagnosis and therapy.

hgtseq: A Standard Pipeline to Study Horizontal Gene Transfer

Horizontal gene transfer (HGT) is well described in prokaryotes: it plays a crucial role in evolution, and has functional consequences in insects and plants. However, less is known about HGT in humans. Studies have reported bacterial integrations in cancer patients, and microbial sequences have been detected in data from well-known human sequencing projects. Few of the existing tools for investigating HGT are highly automated. Thanks to the adoption of Nextflow for life sciences workflows, and to the standards and best practices curated by communities such as nf-core, fully automated, portable, and scalable pipelines can now be developed. Here we present nf-core/hgtseq to facilitate the analysis of HGT from sequencing data in different organisms. We showcase its performance by analysing six exome datasets from five mammals. Hgtseq can be run seamlessly in any computing environment and accepts data generated by existing exome and whole-genome sequencing projects; this will enable researchers to expand their analyses into this area. Fundamental questions are still open about the mechanisms and the extent or role of horizontal gene transfer: by releasing hgtseq we provide a standardised tool which will enable a systematic investigation of this phenomenon, thus paving the way for a better understanding of HGT.

Treasures from trash in cancer research

INTRODUCTION

Cancer research has significantly improved in recent years, primarily due to next-generation sequencing (NGS) technology. Consequently, an enormous amount of genomic and transcriptomic data has been generated. In most cases, the data needed for research goals are used, and unwanted reads are discarded. However, these eliminated data contain relevant information. Aiming to test this hypothesis, genomic and transcriptomic data were acquired from public datasets.

MATERIALS AND METHODS

Metagenomic tools were used to explore genomic cancer data; additional annotations were used to explore differentially expressed ncRNAs from miRNA experiments, and variants in adjacent to tumor samples from RNA-seq experiments were also investigated.

RESULTS

In all analyses, new data were obtained: from DNA-seq data, microbiome taxonomies were characterized with a similar performance of dedicated metagenomic research; from miRNA-seq data, additional differentially expressed sncRNAs were found; and in tumor and adjacent to tumor tissue data, somatic variants were found.

CONCLUSIONS

These findings indicate that unexplored data from NGS experiments could help elucidate carcinogenesis and discover putative biomarkers with clinical applications. Further investigations should be considered for experimental design, providing opportunities to optimize data, saving time and resources while granting access to multiple genomic perspectives from the same sample and experimental run.

De novo identification of microbial contaminants in low microbial biomass microbiomes with Squeegee

Computational analysis of host-associated microbiomes has opened the door to numerous discoveries relevant to human health and disease. However, contaminant sequences in metagenomic samples can potentially impact the interpretation of findings reported in microbiome studies, especially in low-biomass environments. Contamination from DNA extraction kits or sampling lab environments leaves taxonomic "bread crumbs" across multiple distinct sample types. Here we describe Squeegee, a de novo contamination detection tool that is based upon this principle, allowing the detection of microbial contaminants when negative controls are unavailable. On the low-biomass samples, we compare Squeegee predictions to experimental negative control data and show that Squeegee accurately recovers putative contaminants. We analyze samples of varying biomass from the Human Microbiome Project and identify likely, previously unreported kit contamination. Collectively, our results highlight that Squeegee can identify microbial contaminants with high precision and thus represents a computational approach for contaminant detection when negative controls are unavailable.

Comprehensive Phenotyping in Inflammatory Bowel Disease: Search for Biomarker Algorithms in the Transkingdom Interactions Context

Inflammatory bowel disease (IBD) is the most common form of intestinal inflammation associated with a dysregulated immune system response to the commensal microbiota in a genetically susceptible host. IBD includes ulcerative colitis (UC) and Crohn's disease (CD), both of which are remarkably heterogeneous in their clinical presentation and response to treatment. This translates into a notable diagnostic challenge, especially in underdeveloped countries where IBD is on the rise and access to diagnosis or treatment is not always accessible for chronic diseases. The present work characterized, for the first time in our region, epigenetic biomarkers and gut microbial profiles associated with UC and CD patients in the Buenos Aires Metropolitan area and revealed differences between non-IBD controls and IBD patients. General metabolic functions associated with the gut microbiota, as well as core microorganisms within groups, were also analyzed. Additionally, the gut microbiota analysis was integrated with relevant clinical, biochemical and epigenetic markers considered in the follow-up of patients with IBD, with the aim of generating more powerful diagnostic tools to discriminate phenotypes. Overall, our study provides new insights into data analysis algorithms to promote comprehensive phenotyping tools using quantitative and qualitative analysis in a transkingdom interactions network context.

Impact of exposure to arsenic on the bacterial microbiota associated with river biofilms in the Pampas region

Freshwater contamination by arsenic (As) is a worldwide problem. It may be found in Pampean streams of Argentina at concentrations higher than those recommended by international organizations and stipulated by national regulations. Exposure to high As concentrations causes serious consequences to both human health and the environment. The general objective of this work was to evaluate the effect of As on the biofilm microbiota structure from Naveira stream, Luján, Province of Buenos Aires (Coordinates: 34º34'02″ S 59º03'51″ W). The biofilm collected was cultivated in glass aquaria at different As III concentrations (0, 0.2 and 20 mg / L), inside incubation chambers under controlled conditions (16 h light: 8 h dark and 24 ± 1 °C) and constant aeration for 31 d, with partial water renewal every 9 d. We amplified the hypervariable regions V3 and V4 of the bacterial 16S rRNA gene from biofilm bacterial community samples to determine the diversity and abundance of the different taxa. The taxonomic composition of each sample, the alpha diversity of each treatment and the main metabolic pathways were analyzed. Principal Component Analysis of the present phyla and a Linear Discriminant Analysis of the metabolic pathways was also performed. Significant changes were observed in relation to the taxonomic composition of the bacterial community after exposure to the metalloid. However, this effect was not observed at the low concentration used (0.2 mg / L), which is the one that corresponds to ecologically relevant levels. The significantly affected phyla were Verrucomicrobiota, Acidobacteriota, Patescibacteria, Hydrogenedentes and WPS-2. The relative abundances of the Verrucomicrobiota, WPS-2 and Patescibacteria groups were notably decreased in the treatment with high As, while the Acidobacteria group was increased in both treatments with As. The stream samples showed greater bacterial diversity than those grown in the laboratory without As. Finally, it was possible to characterize the metabolic profile of the biofilm developed under natural conditions in the leaves of the aquatic plant Elodea canadensis in the Naveira stream. In addition, results showed that biosynthesis-related pathways were more abundant at the high As concentration treatment (20 mg / L).

Quantification and characterization of mouse and human tissue-resident microbiota by qPCR and 16S sequencing

The tissue-resident microbiota is an integral component of multiple tumor types, but it remains challenging to characterize its abundance and composition due to its low biomass. Here, we describe an optimized protocol for quantification and profiling of tissue-resident microbiota. The major optimized steps include DNA extraction, qPCR, 16S library construction, and bioinformatics analysis. This protocol enables robust and accurate characterization of the dynamics of normal and tumor tissue-resident microbiota at its physiological abundance from both mouse and human origins. For complete details on the use and execution of this protocol, please refer to Fu et al. (2022).

Postnatal exposure to ambient air pollutants is associated with the composition of the infant gut microbiota at 6-months of age

Epidemiological studies in adults have shown that exposure to ambient air pollution (AAP) is associated with the composition of the adult gut microbiome, but these relationships have not been examined in infancy. We aimed to determine if 6-month postnatal AAP exposure was associated with the infant gut microbiota at 6 months of age in a cohort of Latino mother-infant dyads from the Southern California Mother's Milk Study (n = 103). We estimated particulate matter (PM_2.5 and PM₁₀) and nitrogen dioxide (NO₂) exposure from birth to 6-months based on residential address histories. We characterized the infant gut microbiota using 16S rRNA amplicon sequencing at 6-months of age. At 6-months, the gut microbiota was dominated by the phyla Bacteroidetes, Firmicutes, Proteobacteria, and Actinobacteria. Our results show that, after adjusting for important confounders, postnatal AAP exposure was associated with the composition of the gut microbiota. As an example, PM₁₀ exposure was positively associated with Dialister, Dorea, Acinetobacter, and Campylobacter while PM_2.5 was positively associated with Actinomyces. Further, exposure to PM₁₀ and PM_2.5 was inversely associated with Alistipes and NO₂ exposure was positively associated with Actinomyces, Enterococcus, Clostridium, and Eubacterium. Several of these taxa have previously been linked with systemic inflammation, including the genera Dialister and Dorea. This study provides the first evidence of significant associations between exposure to AAP and the composition of the infant gut microbiota, which may have important implications for future infant health and development.

Lincomycin Administration against Persistent Multi-Drug Resistant Chronic Endometritis in Infertile Women with a History of Repeated Implantation Failure

Chronic endometritis (CE) is an infectious disease of the uterine lining, which is characterized by endometrial stromal plasmacyte (ESPC) infiltration. CE is often seen in infertile women with a history of repeated implantation failure (RIF) following an in vitro fertilization-embryo transfer program, recurrent pregnancy loss, and unknown etiology. Oral antibiotic agents, such as doxycycline, metronidazole, ciprofloxacin, azithromycin, and moxifloxacin, have been prescribed and are effective in the treatment of CE. Multi-drug resistance (MDR), however, is an emerging issue, as in other medical fields. We report six cases of persistent MDR-CE in infertile women who were resistant to all the aforementioned antibiotic agents. The bacterial genera and microbial communities unique to persistent MDR-CE were not identified in their vaginal secretions and/or endometrial fluid. Oral lincomycin administration (14 days, 1500 mg/day) was effective in the eradication of ESPCs in these women. In the embryo transfer cycles following histopathologic confirmation of cure (elimination of ESPCs) of persistent MDR-CE, three out of them had a successful live birth.

The human "contaminome": bacterial, viral, and computational contamination in whole genome sequences from 1000 families

The unmapped readspace of whole genome sequencing data tends to be large but is often ignored. We posit that it contains valuable signals of both human infection and contamination. Using unmapped and poorly aligned reads from whole genome sequences (WGS) of over 1000 families and nearly 5000 individuals, we present insights into common viral, bacterial, and computational contamination that plague whole genome sequencing studies. We present several notable results: (1) In addition to known contaminants such as Epstein-Barr virus and phiX, sequences from whole blood and lymphocyte cell lines contain many other contaminants, likely originating from storage, prep, and sequencing pipelines. (2) Sequencing plate and biological sample source of a sample strongly influence contamination profile. And, (3) Y-chromosome fragments not on the human reference genome commonly mismap to bacterial reference genomes. Both experiment-derived and computational contamination is prominent in next-generation sequencing data. Such contamination can compromise results from WGS as well as metagenomics studies, and standard protocols for identifying and removing contamination should be developed to ensure the fidelity of sequencing-based studies.

Bacterial DNA Detection in the Blood of Healthy Subjects

Background:

The presence of microbiome in the blood samples of healthy individuals has been addressed. However, no information can be found on the healthy human blood microbiome of Iranian subjects. The current study is thus aimed to investigate the existence of bacteria or bacterial DNA in healthy individuals.

Methods:

Blood samples of healthy subjects were incubated in BHI broth at 37 °C for 72 h. The 16S rRNA PCR and sequencing were performed to analyze bacterial isolates. The 16S rRNA PCR was directly carried out on DNA samples extracted from the blood of healthy individuals. NGS was conducted on blood samples with culture-positive results.

Results:

Fifty blood samples were tested, and six samples were positive by culture as confirmed by Gram staining and microscopy. The obtained 16S rRNA sequences of cultured bacterial isolates revealed the presence of Bacilli and Staphylococcus species by clustering in the GeneBank database (≥97% identity). The 16S rRNA gene sequencing results of one non-cultured blood specimen showed the presence of Burkholderia. NGS results illustrated the presence of Romboutsia, Lactobacillus, Streptococcus, Bacteroides, and Staphylococcus in the blood samples of positive cultures.

Conclusion:

The dormant blood microbiome of healthy individuals may give the idea that the steady transfer of bacteria into the blood does not necessarily lead to sepsis. However, the origins and identities of blood-associated bacterial rDNA sequences need more evaluation in the healthy population.

Targeting the gut and tumor microbiota in cancer

Microorganisms within the gut and other niches may contribute to carcinogenesis, as well as shaping cancer immunosurveillance and response to immunotherapy. Our understanding of the complex relationship between different host-intrinsic microorganisms, as well as the multifaceted mechanisms by which they influence health and disease, has grown tremendously-hastening development of novel therapeutic strategies that target the microbiota to improve treatment outcomes in cancer. Accordingly, the evaluation of a patient's microbial composition and function and its subsequent targeted modulation represent key elements of future multidisciplinary and precision-medicine approaches. In this Review, we outline the current state of research toward harnessing the microbiome to better prevent and treat cancer.

Tumor-resident intracellular microbiota promotes metastatic colonization in breast cancer

Tumor-resident intracellular microbiota is an emerging tumor component that has been documented for a variety of cancer types with unclear biological functions. Here, we explored the functional significance of these intratumor bacteria, primarily using a murine spontaneous breast-tumor model MMTV-PyMT. We found that depletion of intratumor bacteria significantly reduced lung metastasis without affecting primary tumor growth. During metastatic colonization, intratumor bacteria carried by circulating tumor cells promoted host-cell survival by enhancing resistance to fluid shear stress by reorganizing actin cytoskeleton. We further showed that intratumor administration of selected bacteria strains isolated from tumor-resident microbiota promoted metastasis in two murine tumor models with significantly different levels of metastasis potential. Our findings suggest that tumor-resident microbiota, albeit at low biomass, play an important role in promoting cancer metastasis, intervention of which might therefore be worth exploring for advancing oncology care.

FrogCap: A modular sequence capture probe-set for phylogenomics and population genetics for all frogs, assessed across multiple phylogenetic scales

Despite the prevalence of high-throughput sequencing in phylogenetics, many relationships remain difficult to resolve because of conflicting signal among genomic regions. Selection of different types of molecular markers from different genomic regions is required to overcome these challenges. For evolutionary studies in frogs, we introduce the publicly available FrogCap suite of genomic resources, which is a large collection of ~15,000 markers that unifies previous genetic sequencing efforts. FrogCap is designed to be modular, such that subsets of markers and SNPs can be selected based on the desired phylogenetic scale. FrogCap uses a variety of marker types that include exons and introns, ultraconserved elements, and previously sequenced Sanger markers, which span up to 10,000 bp in alignment lengths; in addition, we demonstrate potential for SNP-based analyses. We tested FrogCap using 121 samples distributed across five phylogenetic scales, comparing probes designed using a consensus- or exemplar genome-based approach. Using the consensus design is more resilient to issues with sensitivity, specificity, and missing data than picking an exemplar genome sequence. We also tested the impact of different bait kit sizes (20,020 vs. 40,040) on depth of coverage and found triple the depth for the 20,020 bait  kit. We observed sequence capture success (i.e., missing data, sequenced markers/bases, marker length, and informative sites) across phylogenetic scales. The incorporation of different marker types is effective for deep phylogenetic relationships and shallow population genetics studies. Having demonstrated FrogCap's utility and modularity, we conclude that these new resources are efficacious for high-throughput sequencing projects across variable timescales.

Differential Vaginal Microbiota Profiling in Lactic-Acid-Producing Bacteria between Infertile Women with and without Chronic Endometritis

Purpose: Chronic endometritis (CE) is an infectious and inflammatory disorder associated with infertility of unknown etiology, repeated implantation failure, and recurrent pregnancy loss. In the current clinical practice, intrauterine interventions such as endometrial biopsy/histopathologic examinations and/or hysteroscopy are required for the diagnosis of CE. In this study, we analyzed the microbiota in vaginal secretions (VS) as a potential prediction tool for CE in infertile women. Methods: Using next-generation sequencing analysis, we compared the VS and endometrial fluid (EF) microbiota in infertile women with (n = 20) or without CE (n = 103). Results: The detection rate of Streptococcus and Enterococcus as well as the bacterial abundance of Atopobium and Bifidobacterium in the VS microbiota was significantly lower in the CE group than in the non-CE group. Meanwhile, the detection rate and bacterial abundance of Lactobacillus in the EF and VS microbiota were at similar levels between the two groups. Conclusion: These findings suggest that VS microbiota in infertile women with CE is characterized by the reduction in Bifidobacterium and lactic-acid-producing bacteria other than Lactobacillus. Our results hold promise for the prediction of CE, not by somewhat interventional intrauterine procedures, but by less invasive VS sampling. TRIAL REGISTRATION NUMBER: UMIN000029449 (registration date 6 October 2017).

A Two-Time Point Analysis of Gut Microbiota in the General Population of Buenos Aires and Its Variation Due to Preventive and Compulsory Social Isolation During the COVID-19 Pandemic

The COVID-19 pandemic poses a great challenge to global public health. The extraordinary daily use of household disinfectants and cleaning products, social distancing and the loss of everyday situations that allow contact between individuals, have a direct impact on the transfer of microorganisms within the population. Together, these changes, in addition to those that occur in eating habits, can affect the composition and diversity of the gut microbiota. A two-time point analysis of the fecal microbiota of 23 Metropolitan Buenos Aires (BA) inhabitants was carried out, to compare pre-pandemic data and its variation during preventive and compulsory social isolation (PCSI) in 2020. To this end, 23 healthy subjects, who were previously studied by our group in 2016, were recruited for a second time during the COVID-19 pandemic, and stool samples were collected from each subject at each time point (n = 46). The hypervariable region V3-V4 of the 16S rRNA gene was high-throughput sequenced. We found significant differences in the estimated number of observed features (p < 0.001), Shannon entropy index (p = 0.026) and in Faith phylogenetic diversity (p < 0.001) between pre-pandemic group (PPG) vs. pandemic group (PG), being significantly lower in the PG. Although no strong change was observed in the core microbiota between the groups in this study, a significant decrease was observed during PCSI in the phylum Verrucomicrobia, which contributes to intestinal health and glucose homeostasis. Microbial community structure (beta diversity) was also compared between PPG and PG. The differences observed in the microbiota structure by unweighted UniFrac PCoA could be explained by six differential abundant genera that were absent during PCSI. Furthermore, putative functional genes prediction using PICRUSt infers a smaller predicted prevalence of genes in the intestinal tryptophan, glycine-betaine, taurine, benzoate degradation, as well as in the synthesis of vitamin B12 during PCSI. This data supports the hypothesis that the microbiome of the inhabitants of BA changed in the context of isolation during PCSI. Therefore, these results could increase the knowledge necessary to propose strategic nutraceutical, functional food, probiotics or similar interventions that contribute to improving public health in the post-pandemic era.

Formalin-Fixed Paraffin-Embedded (FFPE) samples are not a beneficial replacement for frozen tissues in fetal membrane microbiota research

Formalin-Fixed Paraffin-Embedded (FFPE) tissues are routinely collected, archived, and used for clinical diagnosis, including maternal and neonatal health. Applying FFPE samples to microbiota research would be beneficial to reduce preparation, storage and costs associated with limited available frozen samples. This research aims to understand if FFPE fetal membrane samples are comparable to frozen tissues, which are the current gold standard for DNA microbiota analysis. Extracted DNA from nine matched paired patients were sequenced by Illumina sequencing of the V4 16S rRNA gene region. This included duplicate frozen amnion and chorion fetal membrane rolls or FFPE combined amniochorionic samples. Negative controls of surrounding wax blocks and DNA extraction reagents were processed alongside samples using identical methods. DNA quality and quantity was assessed by NanoDrop, agarose gel electrophoresis and Bioanalyzer. Decontam and SourceTracker were integrated into microbiota analysis to identify the presence of contaminating sources. The bacterial profile and nine genera differed between FFPE and frozen fetal membranes. There were no differences in bacterial profiles between FFPE samples and corresponding wax negative controls, with 49% of bacteria in FFPE fetal membrane samples matched to the source origin of paraffin wax, and 40% originating from DNA extraction reagent sources. FFPE samples displayed high fragmentation and low quantity of extracted DNA compared to frozen samples. The microbiota of FFPE fetal membrane samples is influenced by processing methods, with the inability to differentiate between the microbiota of the tissue sample and the surrounding wax block. Illumina sequencing results of FFPE and frozen fetal membrane samples should not be compared using the methods employed here. Variation could be influenced by limitations including storage time, DNA extraction and purification methods. To utilise FFPE fetal membrane samples in microbiota research then contamination prevention and detection methods must be included into optimised and standardised protocols, with recommendations presented here.

Differences in microbial profile of endometrial fluid and tissue samples in women with in vitro fertilization failure are driven by Lactobacillus abundance

INTRODUCTION

The endometrial microbiota has been linked to several gynecological disorders, including infertility. It has been shown that the microbial profile of endometrium could have a role in fertilization and pregnancy outcomes. In this study we aim to assess the microbial community of endometrial tissue (ET) and endometrial fluid (EF) samples in women receiving in vitro fertilization (IVF) treatment. We also search for possible associations between chronic endometritis (CE) and endometrial microbiota.

MATERIAL AND METHODS

This was a cohort study involving 25 women aged between 28 and 42 years with both primary and secondary infertility and with at least one IVF failure. The ET and EF sample collection was carried out between September 2016 and November 2018. Each of the participants provided two types of samples-tissue and fluid samples (50 samples in total). A 16S rRNA sequencing was performed on both of the sample types for microbial profile evaluation. CE was diagnosed based on a CD138 immunohistochemistry where CE diagnosis was confirmed in the presence of one or more plasma cells. Microbial profiles of women with and without CE were compared in both sample types separately.

RESULTS

We report no differences in the microbial composition and alpha diversity (p_Observed  = 0.07, p_Shannon  = 0.65, p_{Inverse Simpson}  = 0.59) between the EF and ET samples of IVF patients. We show that the abundance of the genus Lactobacillus influences the variation in microbial beta diversity between and fluid samples (r²  = 0.34; false discovery rate [FDR] <9.9 × 10^-5 ). We report that 32% (8/25) of the participants had differences in Lactobacillus dominance in the paired samples and these samples also present a different microbial diversity (p_Shannon  = 0.06, FDR_{weighted UniFrac}  = 0.01). These results suggest that the microbial differences between ET and fluid samples are driven by the abundance of genus Lactobacillus. The microbiome of CE and without CE (ie non-CE) women in our sample set of IVF patients was similar.

CONCLUSIONS

Our findings show that genus Lactobacillus dominance is an important factor influencing the microbial composition of ET and fluid samples.

Presence of periodontal pathogenic bacteria in blood of patients with coronary artery disease

It has been hypothesised that oral bacteria can migrate, through the blood, from the mouth to the arterial plaques, thus exacerbating atherosclerosis. This study compared bacteria present in the peripheral blood of individuals with and without coronary artery disease (CAD). RNA sequences obtained from blood were downloaded from GEO (GSE58150). Eight patients with coronary artery calcification (CAC) scoring > 500 and eight healthy individuals were analysed. After conducting quality control, the sequences were aligned to the hg38 reference genome using Hisat2. Bacterial taxa were analysed by inputting the unmapped sequences into Kraken. Ecological indices were calculated using Vegan. The package DESeq2 was used to compare the counts of bacteria per standard rank between groups. A total of 51 species were found only in patients with CAD and 41 were exclusively present in healthy individuals. The counts of one phylum, one class, three orders, two families and one genus were significantly different between the analysed groups (p < 0.00032, FDR < 10%), including the orders Cardiobacteriales, Corynebacteriales and Fusobacteriales. Twenty-three bacterial species belonging to the subgingival plaque bacterial complexes were also identified in the blood of individuals from both the groups; Fusobacterium nucleatum was significantly less frequent in patients with CAD (p = 0.0012, FDR = 4.8%). Furthermore, the frequency of another 11 bacteria differed significantly among patients with CAD than that among healthy individuals (p < 0.0030, FDR < 10%). These bacteria have not been previously reported in patients with atherosclerosis and periodontitis. The presence of members of the subgingival plaque bacterial complexes in the blood of patients with CAC supports the hypothesis that the periodontopathogens can be disseminated through the blood flow to other body parts where they may enhance inflammatory processes that can lead to the development or exacerbation of atherosclerosis.

Maternal and early life exposures and their potential to influence development of the microbiome

At the dawn of the twentieth century, the medical care of mothers and children was largely relegated to family members and informally trained birth attendants. As the industrial era progressed, early and key public health observations among women and children linked the persistence of adverse health outcomes to poverty and poor nutrition. In the time hence, numerous studies connecting genetics ("nature") to public health and epidemiologic data on the role of the environment ("nurture") have yielded insights into the importance of early life exposures in relation to the occurrence of common diseases, such as diabetes, allergic and atopic disease, cardiovascular disease, and obesity. As a result of these parallel efforts in science, medicine, and public health, the developing brain, immune system, and metabolic physiology are now recognized as being particularly vulnerable to poor nutrition and stressful environments from the start of pregnancy to 3 years of age. In particular, compelling evidence arising from a diverse array of studies across mammalian lineages suggest that modifications to our metagenome and/or microbiome occur following certain environmental exposures during pregnancy and lactation, which in turn render risk of childhood and adult diseases. In this review, we will consider the evidence suggesting that development of the offspring microbiome may be vulnerable to maternal exposures, including an analysis of the data regarding the presence or absence of a low-biomass intrauterine microbiome.

A systematic review of the factors influencing microbial colonization of the preterm infant gut

Prematurity coupled with the necessary clinical management of preterm (PT) infants introduces multiple factors that can interfere with microbial colonization. This study aimed to review the perinatal, physiological, pharmacological, dietary, and environmental factors associated with gut microbiota of PT infants. A total of 587 articles were retrieved from a search of multiple databases. Sixty studies were included in the review after removing duplicates and articles that did not meet the inclusion criteria. Review of this literature revealed that evidence converged on the effect of postnatal age, mode of delivery, use of antibiotics, and consumption of human milk in the composition of gut microbiota of PT infants. Less evidence was found for associations with race, sex, use of different fortifiers, macronutrients, and other medications. Future studies with rich metadata are needed to further explore the impact of the PT exposome on the development of the microbiota in this high-risk population.

Endometrial microbiota composition is associated with reproductive outcome in infertile patients

BACKGROUND

Previous evidence indicates associations between the female reproductive tract microbiome composition and reproductive outcome in infertile patients undergoing assisted reproduction. We aimed to determine whether the endometrial microbiota composition is associated with reproductive outcomes of live birth, biochemical pregnancy, clinical miscarriage or no pregnancy.

METHODS

Here, we present a multicentre prospective observational study using 16S rRNA gene sequencing to analyse endometrial fluid and biopsy samples before embryo transfer in a cohort of 342 infertile patients asymptomatic for infection undergoing assisted reproductive treatments.

RESULTS

A dysbiotic endometrial microbiota profile composed of Atopobium, Bifidobacterium, Chryseobacterium, Gardnerella, Haemophilus, Klebsiella, Neisseria, Staphylococcus and Streptococcus was associated with unsuccessful outcomes. In contrast, Lactobacillus was consistently enriched in patients with live birth outcomes.

CONCLUSIONS

Our findings indicate that endometrial microbiota composition before embryo transfer is a useful biomarker to predict reproductive outcome, offering an opportunity to further improve diagnosis and treatment strategies. Video Abstract.

The hidden universe of human milk microbiome: origin, composition, determinants, role, and future perspectives

Although traditionally considered sterile, human milk is currently recognized as an alive ecosystem that harbors not only bacteria, but also viruses, fungi and yeasts, and minor genera, collectively known as the human milk microbiome (HMM). The seeding of HMM is a complex phenomenon whose dynamics are still a matter of research. Many factors contribute to its determination, both maternal, neonatal, environmental, and related to human milk itself. The transmission of microorganisms to the infant through breastfeeding may impact its present and future health, mainly shaping the GI tract microbiome and immune system. The existence and persistence of HMM as a conserved feature among different species may also have an evolutionary meaning, which will become apparent only in evolutionary times.

CONCLUSION

The complexities of HMM warrant further research in order to deepen our knowledge on its origin, determinants, and impact on infants' health. The practical and translational implications of research on HMM (e.g., reconstitution of donor human milk through inoculation of infant's own mother milk, modulation of HMM through maternal dietary supplementation) should not be overlooked.

WHAT IS KNOWN

• Human milk harbors a wide variety of microorganisms, ranging from bacteria to viruses, fungi and yeasts, and minor genera. • Human milk microbiome is shaped over time by many factors: maternal, neonatal, environmental, and related to human milk itself. • The transmission of microorganisms through breastfeeding may impact the infant's present and future health.

WHAT IS NEW

• We provide an overview on human milk microbiome, hopefully encouraging physicians to consider it among the other better-known breastfeeding benefits. • Further studies, with standardized and rigorous study designs to enhance accuracy and reproducibility of the results, are needed to deepen our knowledge of the human milk microbiota and its role in newborn and infant's health.