Contamination in Low Microbial Biomass Microbiome Studies: Issues and Recommendations

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.

The oral cancer microbiome contains tumor space-specific and clinicopathology-specific bacteria

The crosstalk between the oral microbiome and oral cancer has yet to be characterized. This study recruited 218 patients for clinicopathological data analysis. Multiple types of specimens were collected from 27 patients for 16S rRNA gene sequencing, including 26 saliva, 16 swabs from the surface of tumor tissues, 16 adjacent normal tissues, 22 tumor outer tissue, 22 tumor inner tissues, and 10 lymph nodes. Clinicopathological data showed that the pathogenic bacteria could be frequently detected in the oral cavity of oral cancer patients, which was positively related to diabetes, later T stage of the tumor, and the presence of cervical lymphatic metastasis. Sequencing data revealed that compared with adjacent normal tissues, the microbiome of outer tumor tissues had a greater alpha diversity, with a larger proportion of Fusobacterium, Prevotella, and Porphyromonas, while a smaller proportion of Streptococcus. The space-specific microbiome, comparing outer tumor tissues with inner tumor tissues, suggested minor differences in diversity. However, Fusobacterium, Neisseria, Porphyromonas, and Alloprevotella were more abundant in outer tumor tissues, while Prevotella, Selenomonas, and Parvimonas were enriched in inner tumor tissues. Clinicopathology-specific microbiome analysis found that the diversity was markedly different between negative and positive extranodal extensions, whereas the diversity between different T-stages and N-stages was slightly different. Gemella and Bacillales were enriched in T1/T2-stage patients and the non-lymphatic metastasis group, while Spirochaetae and Flavobacteriia were enriched in the extranodal extension negative group. Taken together, high-throughput DNA sequencing in combination with clinicopathological features facilitated us to characterize special patterns of oral tumor microbiome in different disease developmental stages.

Uromycobiome in infants and toddlers with and without urinary tract infections

BACKGROUND

The bacterial components of the urobiome have been described in children, both with and without urinary tract infections (UTI). However, less is known about the pediatric uromycobiome: the community of fungi in the urine. The objectives of this study were to describe the uromycobiome in children and determine whether the uromycobiome differs between children with and without UTI.

METHODS

This was a cross-sectional study of febrile children less than 3 years of age who presented to the Emergency Department and had a catheterized urine sample sent as part of clinical care. We obtained residual urine for use in this study and identified components of the uromyobiome through amplification and sequencing of the fungal ITS2 region. We then compared the uromycobiome between those with and without UTI.

RESULTS

We included 374 children in this study (UTI = 50, no UTI = 324). Fungi were isolated from urine samples of 310 (83%) children. Fungi were identified in a higher proportion of children with UTI, compared to those without UTI (96% vs. 81%, p = 0.01). Shannon diversity index was higher in children with UTI, compared to those without (p = 0.04). Although there were differences in the most abundant taxa between children with and without UTI, there was no significant difference in beta diversity between groups.

CONCLUSIONS

Fungi were detected in the majority of catheterized urine samples from children. While a higher proportion of children with UTI had fungi in their urine, compared to children without UTI, there was no difference in the composition of these groups. A higher resolution version of the Graphical abstract is available as Supplementary information.

Nanopore Sequencing Using the Full-Length 16S rRNA Gene for Detection of Blood-Borne Bacteria in Dogs Reveals a Novel Species of Hemotropic Mycoplasma

Dogs across the globe are afflicted by diverse blood- and vector-borne bacteria (VBB), many of which cause severe disease and can be fatal. Diagnosis of VBB infections can be challenging due to the low concentration of bacteria in the blood, the frequent occurrence of coinfections, and the wide range of known, emerging, and potentially novel VBB species encounterable. Therefore, there is a need for diagnostics that address these challenges by being both sensitive and capable of detecting all VBB simultaneously. We detail the first employment of a nanopore-based sequencing methodology conducted on the Oxford Nanopore Technologies (ONT) MinION device to accurately elucidate the "hemobacteriome" from canine blood through sequencing of the full-length 16S rRNA gene. We detected a diverse range of important canine VBB, including Ehrlichia canis, Anaplasma platys, Mycoplasma haemocanis, Bartonella clarridgeiae, "Candidatus Mycoplasma haematoparvum", a novel species of hemotropic mycoplasma, and Wolbachia endosymbionts of filarial worms, indicative of filariasis. Our nanopore-based protocol was equivalent in sensitivity to both quantitative PCR (qPCR) and Illumina sequencing when benchmarked against these methods, achieving high agreement as defined by the kappa statistics (k > 0.81) for three key VBB. Utilizing the ability of the ONT' MinION device to sequence long read lengths provides an excellent alternative diagnostic method by which the hemobacteriome can be accurately characterized to the species level in a way previously unachievable using short reads. We envision our method to be translatable to multiple contexts, such as the detection of VBB in other vertebrate hosts, including humans, while the small size of the MinION device is highly amenable to field use. IMPORTANCE Blood- and vector-borne bacteria (VBB) can cause severe pathology and even be lethal for dogs in many regions across the globe. Accurate characterization of all the bacterial pathogens infecting a canine host is critical, as coinfections are common and emerging and novel pathogens that may go undetected by traditional diagnostics frequently arise. Deep sequencing using devices from Oxford Nanopore Technologies (ONT) provides a solution, as the long read lengths achievable provide species-level taxonomic identification of pathogens that previous short-read technologies could not accomplish. We developed a protocol using ONT' MinION sequencer to accurately detect and classify a wide spectrum of VBB from canine blood at a sensitivity comparable to that of regularly used diagnostics, such as qPCR. This protocol demonstrates great potential for use in biosurveillance and biosecurity operations for the detection of VBB in a range of vertebrate hosts, while the MinION sequencer's portability allows this method to be used easily in the field.

Microbial DNA extraction of high-host content and low biomass samples: Optimized protocol for nasopharynx metagenomic studies

Introduction

Low microbial biomass and high human DNA content in nasopharyngeal aspirate samples hinder comprehensive characterization of microbiota and resistome. We obtained samples from premature infants, a group with increased risk of developing respiratory disorders and infections, and consequently frequent exposure to antibiotics. Our aim was to devise an optimal protocol for handling nasopharyngeal aspirate samples from premature infants, focusing on host DNA depletion and microbiome and resistome characterization.

Methods

Three depletion and three DNA extraction protocols were compared, using RT-PCR and whole metagenome sequencing to determine the efficiency of human DNA removal, taxonomic profiling and assignment of antibiotic resistance genes. Protocols were tested using mock communities, as well as pooled and individual patient samples.

Results

The only extraction protocol to retrieve the expected DNA yield from mock community samples was based on a lytic method to improve Gram positive recovery (MasterPure™). Host DNA content in non-depleted aliquots from pooled patient samples was 99%. Only samples depleted with MolYsis™ showed satisfactory, but varied reduction in host DNA content, in both pooled and individual patient samples, allowing for microbiome and resistome characterisation (host DNA content from 15% to 98%). Other depletion protocols either retrieved too low total DNA yields, preventing further analysis, or failed to reduce host DNA content. By using Mol_MasterPure protocol on aliquots from pooled patient samples, we increased the number of bacterial reads by 7.6 to 1,725.8-fold compared to non-depleted reference samples. PCR results were indicative of achieved microbial enrichment. Individual patient samples processed with Mol_MasterPure protocol varied greatly in total DNA yield, host DNA content (from 40% to 98%), species and antibiotic resistance gene richness.

Discussion

Despite high human DNA and low microbial biomass content in nasopharynx aspirates of preterm infants, we were able to reduce host DNA content to levels compatible with downstream shotgun metagenomic analysis, including bacterial species identification and coverage of antibiotic resistance genes. Whole metagenomic sequencing of microbes colonizing the nasopharynx may contribute to explaining the possible role of airway microbiota in respiratory conditions and reveal carriage of antibiotic resistance genes.

The community ecology perspective of omics data

The measurement of uncharacterized pools of biological molecules through techniques such as metabarcoding, metagenomics, metatranscriptomics, metabolomics, and metaproteomics produces large, multivariate datasets. Analyses of these datasets have successfully been borrowed from community ecology to characterize the molecular diversity of samples (ɑ-diversity) and to assess how these profiles change in response to experimental treatments or across gradients (β-diversity). However, sample preparation and data collection methods generate biases and noise which confound molecular diversity estimates and require special attention. Here, we examine how technical biases and noise that are introduced into multivariate molecular data affect the estimation of the components of diversity (i.e., total number of different molecular species, or entities; total number of molecules; and the abundance distribution of molecular entities). We then explore under which conditions these biases affect the measurement of ɑ- and β-diversity and highlight how novel methods commonly used in community ecology can be adopted to improve the interpretation and integration of multivariate molecular data. Video Abstract.

The Microbiome in PDAC-Vantage Point for Future Therapies?

Microorganisms have been increasingly implicated in the pathogenesis of malignant diseases, potentially affecting different hallmarks of cancer. Despite the fact that we have recently gained tremendous insight into the existence and interaction of the microbiome with neoplastic cells, we are only beginning to understand and exploit this knowledge for the treatment of human malignancies. Pancreatic ductal adenocarcinoma (PDAC) is an aggressive solid tumor with limited therapeutic options and a poor long-term survival. Recent data have revealed fascinating insights into the role of the tumoral microbiome in PDAC, with profound implications for survival and potentially therapeutic outcomes. In this review, we outline the current scientific knowledge about the clinical and translational role of the microbiome in PDAC. We describe the microbial compositions in healthy and tumoral pancreatic tissue and point out four major aspects of the microbiome in PDAC: pathogenesis, diagnosis, treatment, and prognosis. However, caution must be drawn to inherent pitfalls in analyzing the intratumoral microbiome. Among others, contamination with environmental microbes is one of the major challenges. To this end, we discuss different decontamination approaches that are crucial for clinicians and scientists alike to foster applicability and physiological relevance in this translational field. Without a definition of an exact and reproducible intratumoral microbial composition, the exploitation of the microbiome as a diagnostic or therapeutic tool remains theoretical.

An improved workflow for accurate and robust healthcare environmental surveillance using metagenomics

BACKGROUND

Effective surveillance of microbial communities in the healthcare environment is increasingly important in infection prevention. Metagenomics-based techniques are promising due to their untargeted nature but are currently challenged by several limitations: (1) they are not powerful enough to extract valid signals out of the background noise for low-biomass samples, (2) they do not distinguish between viable and nonviable organisms, and (3) they do not reveal the microbial load quantitatively. An additional practical challenge towards a robust pipeline is the inability to efficiently allocate sequencing resources a priori. Assessment of sequencing depth is generally practiced post hoc, if at all, for most microbiome studies, regardless of the sample type. This practice is inefficient at best, and at worst, poor sequencing depth jeopardizes the interpretation of study results. To address these challenges, we present a workflow for metagenomics-based environmental surveillance that is appropriate for low-biomass samples, distinguishes viability, is quantitative, and estimates sequencing resources.

RESULTS

The workflow was developed using a representative microbiome sample, which was created by aggregating 120 surface swabs collected from a medical intensive care unit. Upon evaluating and optimizing techniques as well as developing new modules, we recommend best practices and introduce a well-structured workflow. We recommend adopting liquid-liquid extraction to improve DNA yield and only incorporating whole-cell filtration when the nonbacterial proportion is large. We suggest including propidium monoazide treatment coupled with internal standards and absolute abundance profiling for viability assessment and involving cultivation when demanding comprehensive profiling. We further recommend integrating internal standards for quantification and additionally qPCR when we expect poor taxonomic classification. We also introduce a machine learning-based model to predict required sequencing effort from accessible sample features. The model helps make full use of sequencing resources and achieve desired outcomes. Video Abstract CONCLUSIONS: This workflow will contribute to more accurate and robust environmental surveillance and infection prevention. Lessons gained from this study will also benefit the continuing development of methods in relevant fields.

Examining pathogen DNA recovery across the remains of a 14th century Italian friar (Blessed Sante) infected with Brucella melitensis

OBJECTIVE

To investigate variation in ancient DNA recovery of Brucella melitensis, the causative agent of brucellosis, from multiple tissues belonging to one individual MATERIALS: 14 samples were analyzed from the mummified remains of the Blessed Sante, a 14 ^th century Franciscan friar from central Italy, with macroscopic diagnosis of probable brucellosis.

METHODS

Shotgun sequencing data from was examined to determine the presence of Brucella DNA.

RESULTS

Three of the 14 samples contained authentic ancient DNA, identified as belonging to B. melitensis. A genome (23.81X depth coverage, 0.98 breadth coverage) was recovered from a kidney stone. Nine of the samples contained reads classified as B. melitensis (7-169), but for many the data quality was insufficient to withstand our identification and authentication criteria.

CONCLUSIONS

We identified significant variation in the preservation and abundance of B. melitensis DNA present across multiple tissues, with calcified nodules yielding the highest number of authenticated reads. This shows how greatly sample selection can impact pathogen identification.

SIGNIFICANCE

Our results demonstrate variation in the preservation and recovery of pathogen DNA across tissues. This study highlights the importance of sample selection in the reconstruction of infectious disease burden and highlights the importance of a holistic approach to identifying disease.

LIMITATIONS

Study focuses on pathogen recovery in a single individual.

SUGGESTIONS FOR FURTHER RESEARCH

Further analysis of how sampling impacts aDNA recovery will improve pathogen aDNA recovery and advance our understanding of disease in past peoples.

Possibilities and limitations of using low biomass samples for urologic disease and microbiome research

With the dogma of sterile urine no longer held as truth, numerous studies have implicated distinct changes in microbial diversity and composition to diseased subgroups in both benign and malignant urological diseases, ranging from overactive bladder to bladder and prostate cancer. Further facilitated by novel and effective techniques of urine culture and sequencing, analysis of the genitourinary microbiome holds high potential to identify biomarkers for disease and prognosis. However, the low biomass of samples included in microbiome studies of the urinary tract challenge researchers to draw definitive conclusions, confounded by technical and procedural considerations that must be addressed. Lack of samples and adequate true negative controls can lead to overestimation of microbial influence with clinical relevance. As such, results from currently available studies and assessment of their limitations required a thorough understanding. The purpose of this narrative review was to summarize notable microbiome studies in the field of urology with a focus on significant findings and limitations of study design. Methodological considerations in future research are also discussed.

On the effect of inheritance of microbes in commensal microbiomes

Background

Our current view of nature depicts a world where macroorganisms dwell in a landscape full of microbes. Some of these microbes not only transit but establish themselves in or on hosts. Although hosts might be occupied by microbes for most of their lives, a microbe-free stage during their prenatal development seems to be the rule for many hosts. The questions of who the first colonizers of a newborn host are and to what extent these are obtained from the parents follow naturally.

Results

We have developed a mathematical model to study the effect of the transfer of microbes from parents to offspring. Even without selection, we observe that microbial inheritance is particularly effective in modifying the microbiome of hosts with a short lifespan or limited colonization from the environment, for example by favouring the acquisition of rare microbes.

Conclusion

By modelling the inheritance of commensal microbes to newborns, our results suggest that, in an eco-evolutionary context, the impact of microbial inheritance is of particular importance for some specific life histories.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12862-022-02029-2.

Advances in experimental and computational methodologies for the study of microbial-surface interactions at different omics levels

The study of the biological response of microbial cells interacting with natural and synthetic interfaces has acquired a new dimension with the development and constant progress of advanced omics technologies. New methods allow the isolation and analysis of nucleic acids, proteins and metabolites from complex samples, of interest in diverse research areas, such as materials sciences, biomedical sciences, forensic sciences, biotechnology and archeology, among others. The study of the bacterial recognition and response to surface contact or the diagnosis and evolution of ancient pathogens contained in archeological tissues require, in many cases, the availability of specialized methods and tools. The current review describes advances in in vitro and in silico approaches to tackle existing challenges (e.g., low-quality sample, low amount, presence of inhibitors, chelators, etc.) in the isolation of high-quality samples and in the analysis of microbial cells at genomic, transcriptomic, proteomic and metabolomic levels, when present in complex interfaces. From the experimental point of view, tailored manual and automatized methodologies, commercial and in-house developed protocols, are described. The computational level focuses on the discussion of novel tools and approaches designed to solve associated issues, such as sample contamination, low quality reads, low coverage, etc. Finally, approaches to obtain a systems level understanding of these complex interactions by integrating multi omics datasets are presented.

Next Generation Sequencing Approaches to Characterize the Respiratory Tract Virome

The COVID-19 pandemic and heightened perception of the risk of emerging viral infections have boosted the efforts to better understand the virome or complete repertoire of viruses in health and disease, with a focus on infectious respiratory diseases. Next-generation sequencing (NGS) is widely used to study microorganisms, allowing the elucidation of bacteria and viruses inhabiting different body systems and identifying new pathogens. However, NGS studies suffer from a lack of standardization, in particular, due to various methodological approaches and no single format for processing the results. Here, we review the main methodological approaches and key stages for studies of the human virome, with an emphasis on virome changes during acute respiratory viral infection, with applications for clinical diagnostics and epidemiologic analyses.

Prospect of bacteria for tumor diagnosis and treatment

In recent decades, the comprehensive cancer treatments including surgery, chemotherapy, and radiotherapy have improved the overall survival rate and quality of life of many cancer patients. However, we are still facing many difficult problems in the cancer treatment, such as unpredictable side effects, high recurrence rate, and poor curative effect. Therefore, the better intervention strategies are needed in this field. In recent years, the role and importance of microbiota in a variety of diseases were focused on as a hot research topic, and the role of some intracellular bacteria of cancer cells in carcinogenesis has recently been discovered. The impact of bacteria on cancer is not limited to their contribution to tumorigenesis, but the overall susceptibility of bacteria to subsequent tumor progression, the development of concurrent infections, and the response to anti-cancer therapy have also been found to be affected. Concerns about the contribution of bacteria in the anti-cancer response have inspired researchers to develop bacteria-based anti-cancer treatments. In this paper, we reviewed the main roles of bacteria in the occurrence and development of tumors, and summarized the mechanism of bacteria in the occurrence, development, and clinical anti-tumor treatment of tumors, providing new insights for the in-depth study of the role of bacteria in tumor diagnosis and treatment. This review aims to provide a new perspective for the development of new technologies based on bacteria to enhance anti-tumor immunotherapy.

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.

Fast-tracking bespoke DNA reference database generation from museum collections for biomonitoring and conservation

Despite recent advances in high-throughput DNA sequencing technologies, a lack of locally relevant DNA reference databases limits the potential for DNA-based monitoring of biodiversity for conservation and biosecurity applications. Museums and national collections represent a compelling source of authoritatively identified genetic material for DNA database development, yet obtaining DNA barcodes from long-stored specimens may be difficult due to sample degradation. Here we demonstrate a sensitive and efficient laboratory and bioinformatic process for generating DNA barcodes from hundreds of invertebrate specimens simultaneously via the Illumina MiSeq system. Using this process, we recovered full-length (334) or partial (105) COI barcodes from 439 of 450 (98%) national collection-held invertebrate specimens. This included full-length barcodes from 146 specimens which produced low-yield DNA and no visible PCR bands, and which produced as little as a single sequence per specimen, demonstrating high sensitivity of the process. In many cases, the identity of the most abundant sequences per specimen were not the correct barcodes, necessitating the development of a taxonomy-informed process for identifying correct sequences among the sequencing output. The recovery of only partial barcodes for some taxa indicates a need to refine certain PCR primers. Nonetheless, our approach represents a highly sensitive, accurate and efficient method for targeted reference database generation, providing a foundation for DNA-based assessments and monitoring of biodiversity.

The road not taken: host genetics in shaping intergenerational microbiomes

The early-life gut microbiome is linked to human phenotypes as an imbalanced microbiome of this period is implicated in diseases throughout life. Several determinants of early-life gut microbiome are explored, however, mechanisms of acquisition, colonization, and stability of early-life gut microbiome and their interindividual variability remain elusive. Host genetics play a vital role to shape the gut microbiome and interact with it to modulate individual phenotypes in human studies and animal models. Given the microbial linkage between host generations, we discuss the current state of roles of host genetics in forming intergenerational microbiomes associated with mothers, offspring, and those vertically transmitted, providing a basis for taking into account host genetics in future early-life microbiome research. We further expand our discussion to the bidirectional interactions between host gene expression and microbiome in human health.

Identification of microbial taxa present in Ctenocephalides felis (cat flea) reveals widespread co-infection and associations with vector phylogeny

BACKGROUND

Ctenocephalides felis, the cat flea, is the most common ectoparasite of cats and dogs worldwide. As a cause of flea allergy dermatitis and a vector for two genera of zoonotic pathogens (Bartonella and Rickettsia spp.), the effect of the C. felis microbiome on pathogen transmission and vector survival is of substantial medical importance to both human and veterinary medicine. The aim of this study was to assay the pathogenic and commensal eubacterial microbial communities of individual C. felis from multiple geographic locations and analyze these findings by location, qPCR pathogen prevalence, and flea genetic diversity.

METHODS

16S Next Generation Sequencing (NGS) was utilized to sequence the microbiome of fleas collected from free-roaming cats, and the cox1 gene was used for flea phylogenetic analysis. NGS data were analyzed for 168 individual fleas from seven locations within the US and UK. Given inconsistency in the genera historically reported to constitute the C. felis microbiome, we utilized the decontam prevalence method followed by literature review to separate contaminants from true microbiome members.

RESULTS

NGS identified a single dominant and cosmopolitan amplicon sequence variant (ASV) from Rickettsia and Wolbachia while identifying one dominant Bartonella clarridgeiae and one dominant Bartonella henselae/Bartonella koehlerae ASV. Multiple less common ASVs from these genera were detected within restricted geographical ranges. Co-detection of two or more genera (Bartonella, Rickettsia, and/or Wolbachia) or multiple ASVs from a single genus in a single flea was common. Achromobacter, Peptoniphilus, and Rhodococcus were identified as additional candidate members of the C. felis microbiome on the basis of decontam analysis and literature review. Ctenocephalides felis phylogenetic diversity as assessed by the cox1 gene fell within currently characterized clades while identifying seven novel haplotypes. NGS sensitivity and specificity for Bartonella and Rickettsia spp. DNA detection were compared to targeted qPCR.

CONCLUSIONS

Our findings confirm the widespread coinfection of fleas with multiple bacterial genera and strains, proposing three additional microbiome members. The presence of minor Bartonella, Rickettsia, and Wolbachia ASVs was found to vary by location and flea haplotype. These findings have important implications for flea-borne pathogen transmission and control.

Background Filtering of Clinical Metagenomic Sequencing with a Library Concentration-Normalized Model

Metagenomic next-generation sequencing (mNGS) can accurately detect pathogens in clinical samples. However, wet-lab contamination constrains mNGS analysis and may result in erroneous interpretation of results. Many existing methods rely on large-scale observational microbiome studies and may not be applicable to clinical mNGS tests. By generation of a pretrained profile of common laboratory contaminants, we developed an mNGS noise-filtering model based on the inverse linear relationship between microbial sequencing reads and sample library concentration, named the background elimination and correction by library concentration-normalized (BECLEAN) model. Its efficacy was evaluated with bacteria- and yeast-spiked samples and 28 cerebrospinal fluid (CSF) specimens. The diagnostic accuracy, precision, sensitivity, and specificity of BECLEAN with reference to conventional methods and diagnosis were 92.9%, 86.7%, 100%, and 86.7%, respectively. BECLEAN led to a dramatic reduction of background noise without affecting the true-positive rate and thus can provide a time-saving and convenient tool in various clinical settings. IMPORTANCE Most of the existing methods to remove wet-lab contamination rely on large-scale observational microbiome studies and may not be applicable to clinical mNGS testing in individual cases. In clinical settings, only a handful of samples might be sequenced in a run. The lab-specific microbiome can complicate existing statistical approaches for removing contamination from small-scale clinical metagenomic sequencing data sets; thus, use of a preliminary lab-specific training set is necessary. Our study provides a rapid and accurate background-filtering tool for clinical metagenomic sequencing by generation of a pretrained profile of common laboratory contaminants. Notably, our work demonstrates that the inverse linear relationship between microbial sequencing reads and library concentration can serve to identify true contaminants and evaluate the relative abundance of a taxon in samples by comparing the observed microbial reads to the model-predicted value. Our findings extend the previously published research and demonstrate confirmatory results in clinical settings.

The lower airways microbiota and antimicrobial peptides indicate dysbiosis in sarcoidosis

BACKGROUND

The role of the pulmonary microbiome in sarcoidosis is unknown. The objectives of this study were the following: (1) examine whether the pulmonary fungal and bacterial microbiota differed in patients with sarcoidosis compared with controls; (2) examine whether there was an association between the microbiota and levels of the antimicrobial peptides (AMPs) in protected bronchoalveolar lavage (PBAL).

METHODS

Thirty-five sarcoidosis patients and 35 healthy controls underwent bronchoscopy and were sampled with oral wash (OW), protected BAL (PBAL), and left protected sterile brushes (LPSB). The fungal ITS1 region and the V3V4 region of the bacterial 16S rRNA gene were sequenced. Bioinformatic analyses were performed with QIIME 2. The AMPs secretory leucocyte protease inhibitor (SLPI) and human beta defensins 1 and 2 (hBD-1 and hBD-2), were measured in PBAL by enzyme-linked immunosorbent assay (ELISA).

RESULTS

Aspergillus dominated the PBAL samples in sarcoidosis. Differences in bacterial taxonomy were minor. There was no significant difference in fungal alpha diversity between sarcoidosis and controls, but the bacterial alpha diversity in sarcoidosis was significantly lower in OW (p = 0.047) and PBAL (p = 0.03) compared with controls. The beta diversity for sarcoidosis compared with controls differed for both fungi and bacteria. AMP levels were significantly lower in sarcoidosis compared to controls (SLPI and hBD-1: p < 0.01). No significant correlations were found between alpha diversity and AMPs.

CONCLUSIONS

The pulmonary fungal and bacterial microbiota in sarcoidosis differed from in controls. Lower antimicrobial peptides levels were seen in sarcoidosis, indicating an interaction between the microbiota and the innate immune system. Whether this dysbiosis represents a pathogenic mechanism in sarcoidosis needs to be confirmed in experimental studies. Video Abstract.

Bacterial DNA involvement in carcinogenesis

The incidence of cancer is high worldwide, and biological factors such as viruses and bacteria play an important role in the occurrence of cancer. Helicobacter pylori, human papillomavirus, hepatitis B viruses and other organisms have been identified as carcinogens. Cancer is a disease driven by the accumulation of genome changes. Viruses can directly cause cancer by changing the genetic composition of the human body, such as cervical cancer caused by human papillomavirus DNA integration and liver cancer caused by hepatitis B virus DNA integration. Recently, bacterial DNA has been found around cancers such as pancreatic cancer, breast cancer and colorectal cancer, and the idea that bacterial genes can also be integrated into the human genome has become a hot topic. In the present paper, we reviewed the latest phenomenon and specific integration mechanism of bacterial DNA into the human genome. Based on these findings, we also suggest three sources of bacterial DNA in cancers: bacterial DNA around human tissues, free bacterial DNA in bacteremia or sepsis, and endogenous bacterial DNA in the human genome. Clarifying the theory that bacterial DNA integrates into the human genome can provide a new perspective for cancer prevention and treatment.

Identifying Candidate Circulating RNA Markers for Coronary Artery Disease by Deep RNA-Sequencing in Human Plasma

Advances in RNA sequencing (RNA-Seq) have facilitated transcriptomic analysis of plasma for the discovery of new diagnostic and prognostic markers for disease. We aimed to develop a short-read RNA-Seq protocol to detect mRNAs, long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs) in plasma for the discovery of novel markers for coronary artery disease (CAD) and heart failure (HF). Circulating cell-free RNA from 59 patients with stable CAD (half of whom developed HF within 3 years) and 30 controls was sequenced to a median depth of 108 paired reads per sample. We identified fragments from 3986 messenger RNAs (mRNAs), 164 long non-coding RNAs (lncRNAs), 405 putative novel lncRNAs and 227 circular RNAs in plasma. Circulating levels of 160 mRNAs, 10 lncRNAs and 2 putative novel lncRNAs were altered in patients compared with controls (absolute fold change >1.2, p < 0.01 adjusted for multiple comparisons). The most differentially abundant transcripts were enriched in mRNAs encoded by the mitochondrial genome. We did not detect any differences in the plasma RNA profile between patients who developed HF compared with those who did not. In summary, we show that mRNAs, lncRNAs and circular RNAs can be reliably detected in plasma by deep RNA-Seq. Multiple coding and non-coding transcripts were altered in association with CAD, including several mitochondrial mRNAs, which may indicate underlying myocardial ischaemia and oxidative stress. If validated, circulating levels of these transcripts could potentially be used to help identify asymptomatic individuals with established CAD prior to an acute coronary event.

Tumor microbiome links cellular programs and immunity in pancreatic cancer

Microorganisms are detected in multiple cancer types, including in putatively sterile organs, but the contexts in which they influence oncogenesis or anti-tumor responses in humans remain unclear. We recently developed single-cell analysis of host-microbiome interactions (SAHMI), a computational pipeline to recover and denoise microbial signals from single-cell sequencing of host tissues. Here we use SAHMI to interrogate tumor-microbiome interactions in two human pancreatic cancer cohorts. We identify somatic-cell-associated bacteria in a subset of tumors and their near absence in nonmalignant tissues. These bacteria predominantly pair with tumor cells, and their presence is associated with cell-type-specific gene expression and pathway activities, including cell motility and immune signaling. Modeling results indicate that tumor-infiltrating lymphocytes closely resemble T cells from infected tissue. Finally, using multiple independent datasets, a signature of cell-associated bacteria predicts clinical prognosis. Tumor-microbiome crosstalk may modulate tumorigenesis in pancreatic cancer with implications for clinical management.

Toward efficient and high-fidelity metagenomic data from sub-nanogram DNA: evaluation of library preparation and decontamination methods

BACKGROUND

Shotgun metagenomic sequencing has greatly expanded the understanding of microbial communities in various biological niches. However, it is still challenging to efficiently convert sub-nanogram DNA to high-quality metagenomic libraries and obtain high-fidelity data, hindering the exploration of niches with low microbial biomass.

RESULTS

To cope with this challenge comprehensively, we evaluated the performance of various library preparation methods on 0.5 pg-5 ng synthetic microbial community DNA, characterized contaminants, and further applied different in silico decontamination methods. First, we discovered that whole genome amplification prior to library construction led to worse outcomes than preparing libraries directly. Among different non-WGA-based library preparation methods, we found the endonuclease-based method being generally good for different amounts of template and the tagmentation-based method showing specific advantages with 0.5 pg template, based on evaluation metrics including fidelity, proportion of designated reads, and reproducibility. The load of contaminating DNA introduced by library preparation varied from 0.01 to 15.59 pg for different kits and accounted for 0.05 to 45.97% of total reads. A considerable fraction of the contaminating reads were mapped to human commensal and pathogenic microbes, thus potentially leading to erroneous conclusions in human microbiome studies. Furthermore, the best performing in silico decontamination method in our evaluation, Decontam-either, was capable of recovering the real microbial community from libraries where contaminants accounted for less than 10% of total reads, but not from libraries with heavy and highly varied contaminants.

CONCLUSIONS

This study demonstrates that high-quality metagenomic data can be obtained from samples with sub-nanogram microbial DNA by combining appropriate library preparation and in silico decontamination methods and provides a general reference for method selection for samples with varying microbial biomass.

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).

Microbial Dark Matter: from Discovery to Applications

With the rapid increase of the microbiome samples and sequencing data, more and more knowledge about microbial communities has been gained. However, there is still much more to learn about microbial communities, including billions of novel species and genes, as well as countless spatiotemporal dynamic patterns within the microbial communities, which together form the microbial dark matter. In this work, we summarized the dark matter in microbiome research and reviewed current data mining methods, especially artificial intelligence (AI) methods, for different types of knowledge discovery from microbial dark matter. We also provided case studies on using AI methods for microbiome data mining and knowledge discovery. In summary, we view microbial dark matter not as a problem to be solved but as an opportunity for AI methods to explore, with the goal of advancing our understanding of microbial communities, as well as developing better solutions to global concerns about human health and the environment.

Skin microbiota analysis in patients with anorexia nervosa and healthy-weight controls reveals microbial indicators of healthy weight and associations with the antimicrobial peptide psoriasin

Anorexia nervosa (AN), a psychiatric condition defined by low body weight for age and height, is associated with numerous dermatological conditions. Yet, clinical observations report that patients with AN do not suffer from infectious skin diseases like those associated with primary malnutrition. Cell-mediated immunity appears to be amplified in AN; however, this proinflammatory state does not sufficiently explain the lower incidence of infections. Antimicrobial peptides (AMPs) are important components of the innate immune system protecting from pathogens and shaping the microbiota. In Drosophila melanogaster starvation precedes increased AMP gene expression. Here, we analyzed skin microbiota in patients with AN and age-matched, healthy-weight controls and investigated the influence of weight gain on microbial community structure. We then correlated features of the skin microbial community with psoriasin and RNase 7, two highly abundant AMPs in human skin, to clarify whether an association between AMPs and skin microbiota exists and whether such a relationship might contribute to the resistance to cutaneous infections observed in AN. We find significant statistical correlations between Shannon diversity and the highly abundant skin AMP psoriasin and bacterial load, respectively. Moreover, we reveal psoriasin significantly associates with Abiotrophia, an indicator for the healthy-weight control group. Additionally, we observe a significant correlation between an individual's body mass index and Lactobacillus, a microbial indicator of health. Future investigation may help clarify physiological mechanisms that link nutritional intake with skin physiology.

Sarcoptic mange changes bacterial and fungal microbiota of bare-nosed wombats (Vombatus ursinus)

Background

Sarcoptes scabiei is globally distributed and one of the most impactful mammalian ectoparasites. Sarcoptic mange, caused by infection with S. scabiei, causes disruption of the epidermis and its bacterial microbiota, but its effects on host fungal microbiota and on the microbiota of marsupials in general have not been studied. Here, we (i) examine bacterial and fungal microbiota changes associated with mange in wild bare-nosed wombats (BNWs) and (ii) evaluate whether opportunistic pathogens are potentiated by S. scabiei infection in this species.

Methods

Using Amplicon Sequencing of the 16S rRNA and ITS2 rDNA genes, we detected skin microbiota changes of the bare-nosed wombat (Vombatus ursinus). We compared the alpha and beta diversity among healthy, moderate, and severe disease states using ANOVA and PERMANOVA with nesting. Lastly, we identified taxa that differed between disease states using analysis of composition of microbes (ANCOM) testing.

Results

We detected significant changes in the microbial communities and diversity with mange in BNWs. Severely affected BNWs had lower amplicon sequence variant (ASV) richness compared to that of healthy individuals, and the microbial communities were significantly different between disease states with higher relative abundance of potentially pathogenic microbial taxa in mange-affected BNWs including Staphylococcus sciuri, Corynebacterium spp., Brevibacterium spp., Brachybacterium spp., and Pseudogymnascus spp. and Debaryomyces spp.

Conclusion

This study represents the first investigation of microbial changes in association with sarcoptic mange in a marsupial host, as well as the first investigation of fungal microbial changes on the skin of any host suffering from sarcoptic mange. Our results are broadly consistent with bacterial microbiota changes observed in humans, pigs, canids, and Iberian ibex, suggesting the epidermal microbial impacts of mange may be generalisable across host species. We recommend that future studies investigating skin microbiota changes include both bacterial and fungal data to gain a more complete picture of the effects of sarcoptic mange.

Graphical Abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s13071-022-05452-y.

Assessing the performance of historical skins and bones for museomics using wolf specimens as a case study

Advances in the field of museomics have promoted a high sampling demand for natural history collections (NHCs), eventually resulting in damage to invaluable resources to understand historical biodiversity. It is thus essential to achieve a consensus about which historical tissues present the best sources of DNA. In this study, we evaluated the performance of different historical tissues from Iberian wolf NHCs in genome-wide assessments. We targeted three tissues—bone (jaw and femur), maxilloturbinal bone, and skin—that have been favored by traditional taxidermy practices for mammalian carnivores. Specifically, we performed shotgun sequencing and target capture enrichment for 100,000 single nucleotide polymorphisms (SNPs) selected from the commercial Canine HD BeadChip across 103 specimens from 1912 to 2005. The performance of the different tissues was assessed using metrics based on endogenous DNA content, uniquely high-quality mapped reads after capture, and enrichment proportions. All samples succeeded as DNA sources, regardless of their collection year or sample type. Skin samples yielded significantly higher amounts of endogenous DNA compared to both bone types, which yielded equivalent amounts. There was no evidence for a direct effect of tissue type on capture efficiency; however, the number of genotyped SNPs was strictly associated with the starting amount of endogenous DNA. Evaluation of genotyping accuracy for distinct minimum read depths across tissue types showed a consistent overall low genotyping error rate (&lt;7%), even at low (3x) coverage. We recommend the use of skins as reliable and minimally destructive sources of endogenous DNA for whole-genome and target enrichment approaches in mammalian carnivores. In addition, we provide a new 100,000 SNP capture array validated for historical DNA (hDNA) compatible to the Canine HD BeadChip for high-quality DNA. The increasing demand for NHCs as DNA sources should encourage the generation of genomic datasets comparable among studies.

Do-it-Yourself Mock Community Standard for Multi-Step Assessment of Microbiome Protocols

Microbiomes provide critical functions that support animals, plants, and ecosystems. High-throughput sequencing (HTS) has become an essential tool for the cultivation-independent study of microbiomes found in diverse environments, but requires effective and meaningful controls. One such critical control is a mock microbial community, which is used as a positive control for nucleic acid extraction, marker gene amplification, and sequencing. While mock community standards can be purchased, they can be costly and often include only medically relevant microbial strains that are not expected to be major players in non-human microbiomes. As an alternative, it is possible to design and construct a do-it-yourself (DIY) mock community, which can then be used as a positive control that is specifically customized to the protocol needs of a particular study system. In this article, we describe protocols to select appropriate microbial strains for the construction of a mock community. We first describe the steps to verify the identity of community members via Sanger sequencing. Then, we provide guidance on assembling and storing the DIY mock community as viable whole cells. This includes steps to create standard growth curves referenced to plate counts for each member, so that the community members can be quantified and later compared in terms of their "expected versus returned" relative contributions after sequencing. We also describe appropriate methods for the cryostorage of the fully assembled mock community as viable whole cells, so that they can be used as a unit in a microbiome analysis, from the lysis and nucleic acid extraction steps onwards. Finally, we provide an example of returned data and interpretation of DIY mock community sequences, discussing how to assess possible contamination and identify protocol biases for particular members. Overall, DIY mock communities serve to determine success and possible bias in a cultivation-independent microbiome analysis. © 2022 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Strain identification and verification using Sanger sequencing Basic Protocol 2: Creation of glycerol stocks of each mock community strain for long-term cryostorage Basic Protocol 3: Assessment of strain freezer viability without cryoprotectant Basic Protocol 4: Creation of standard curve to determine CFU/ml of a liquid culture as a function of optical density Basic Protocol 5: Full mock community assembly using community concentration calculations and standard curves.

Towards standardized and reproducible research in skin microbiomes

Skin is a complex organ serving a critical role as a barrier and mediator of interactions between the human body and its environment. Recent studies have uncovered how resident microbial communities play a significant role in maintaining the normal healthy function of the skin and the immune system. In turn, numerous host-associated and environmental factors influence these communities' composition and diversity across the cutaneous surface. In addition, specific compositional changes in skin microbiota have also been connected to the development of several chronic diseases. The current era of microbiome research is characterized by its reliance on large data sets of nucleotide sequences produced with high-throughput sequencing of sample-extracted DNA. These approaches have yielded new insights into many previously uncharacterized microbial communities. Application of standardized practices in the study of skin microbial communities could help us understand their complex structures, functional capacities, and health associations and increase the reproducibility of the research. Here, we overview the current research in human skin microbiomes and outline challenges specific to their study. Furthermore, we provide perspectives on recent advances in methods, analytical tools and applications of skin microbiomes in medicine and forensics.

Exploration and comparison of bacterial communities present in bovine faeces, milk and blood using 16S rRNA metagenomic sequencing

Cattle by-products like faeces, milk and blood have many uses among rural communities; aiding to facilitate everyday household activities and occasional rituals. Ecologically, the body sites from which they are derived consist of distinct microbial communities forming a complex ecosystem of niches. We aimed to explore and compare the faecal, milk and blood microbiota of cows through 16S rRNA sequencing. All downstream analyses were performed using applications in R Studio (v3.6.1). Alpha-diversity metrics showed significant differences between faeces and blood; faeces and milk; but non-significant between blood and milk using Kruskal-Wallis test, P < 0,05. The beta-diversity metrics on Principal Coordinate Analysis and Non-Metric Dimensional Scaling significantly clustered samples by type (PERMANOVA test, P < 0,05). The overall analysis revealed a total of 30 phyla, 74 classes, 156 orders, 243 families and 408 genera. Firmicutes, Bacteroidota and Proteobacteria were the most abundant phyla overall. A total of 58 genus-level taxa occurred concurrently between the body sites. The important taxa could be categorized into four potentially pathogenic clusters i.e. arthropod-borne; food-borne and zoonotic; mastitogenic; and metritic and abortigenic. A number of taxa were significantly differentially abundant (DA) between sites based on the Wald test implemented in DESeq2 package. Majority of the DA taxa (i.e. Romboutsia, Paeniclostridium, Monoglobus, Akkermansia, Turicibacter, Bacteroides, Candidatus_Saccharimonas, UCG-005 and Prevotellaceae_UCG-004) were significantly enriched in faeces in comparison to milk and blood, except for Anaplasma which was greatly enriched in blood and was in turn the largest microbial genus in the entire analysis. This study provides insights into the microbial community composition of the sampled body sites and its extent of overlapping. It further highlights the potential risk of disease occurrence and transmission between the animals and the community of Waaihoek in KwaZulu-Natal, Republic of South Africa pertaining to their unsanitary practices associated with the use of cattle by-products.

A Case Study for the Recovery of Authentic Microbial Ancient DNA from Soil Samples

High Throughput DNA Sequencing (HTS) revolutionized the field of paleomicrobiology, leading to an explosive growth of microbial ancient DNA (aDNA) studies, especially from environmental samples. However, aDNA studies that examine environmental microbes routinely fail to authenticate aDNA, examine laboratory and environmental contamination, and control for biases introduced during sample processing. Here, we surveyed the available literature for environmental aDNA projects—from sample collection to data analysis—and assessed previous methodologies and approaches used in the published microbial aDNA studies. We then integrated these concepts into a case study, using shotgun metagenomics to examine methodological, technical, and analytical biases during an environmental aDNA study of soil microbes. Specifically, we compared the impact of five DNA extraction methods and eight bioinformatic pipelines on the recovery of microbial aDNA information in soil cores from extreme environments. Our results show that silica-based methods optimized for aDNA research recovered significantly more damaged and shorter reads (<100 bp) than a commercial kit or a phenol−chloroform method. Additionally, we described a stringent pipeline for data preprocessing, efficiently decreasing the representation of low-complexity and duplicated reads in our datasets and downstream analyses, reducing analytical biases in taxonomic classification.

Cascading effects of habitat loss on ectoparasite-associated bacterial microbiomes

Suitable habitat fragment size, isolation, and distance from a source are important variables influencing community composition of plants and animals, but the role of these environmental factors in determining composition and variation of host-associated microbial communities is poorly known. In parasite-associated microbial communities, it is hypothesized that evolution and ecology of an arthropod parasite will influence its microbiome more than broader environmental factors, but this hypothesis has not been extensively tested. To examine the influence of the broader environment on the parasite microbiome, we applied high-throughput sequencing of the V4 region of 16S rRNA to characterize the microbiome of 222 obligate ectoparasitic bat flies (Streblidae and Nycteribiidae) collected from 155 bats (representing six species) from ten habitat fragments in the Atlantic Forest of Brazil. Parasite species identity is the strongest driver of microbiome composition. To a lesser extent, reduction in habitat fragment area, but not isolation, is associated with an increase in connectance and betweenness centrality of bacterial association networks driven by changes in the diversity of the parasite community. Controlling for the parasite community, bacterial network topology covaries with habitat patch area and exhibits parasite-species specific responses to environmental change. Taken together, habitat loss may have cascading consequences for communities of interacting macro- and microorgansims.

Current understanding of the human microbiome in glioma

There is mounting evidence that the human microbiome is highly associated with a wide variety of central nervous system diseases. However, the link between the human microbiome and glioma is rarely noticed. The exact mechanism of microbiota to affect glioma remains unclear. Recent studies have demonstrated that the microbiome may affect the development, progress, and therapy of gliomas, including the direct impacts of the intratumoral microbiome and its metabolites, and the indirect effects of the gut microbiome and its metabolites. Glioma-related microbiome (gut microbiome and intratumoral microbiome) is associated with both tumor microenvironment and tumor immune microenvironment, which ultimately influence tumorigenesis, progression, and responses to treatment. In this review, we briefly summarize current knowledge regarding the role of the glioma-related microbiome, focusing on its gut microbiome fraction and a brief description of the intratumoral microbiome, and put forward the prospects in which microbiome can be applied in the future and some challenges still need to be solved.

Metagenome sequencing and 768 microbial genomes from cold seep in South China Sea

Cold seep microbial communities are fascinating ecosystems on Earth which provide unique models for understanding the living strategies in deep-sea distinct environments. In this study, 23 metagenomes were generated from samples collected in the Site-F cold seep field in South China Sea, including the sea water closely above the invertebrate communities, the cold seep fluids, the fluids under the invertebrate communities and the sediment column around the seep vent. By binning tools, we retrieved a total of 768 metagenome assembled genome (MAGs) that were estimated to be >60% complete. Of the MAGs, 61 were estimated to be >90% complete, while an additional 105 were >80% complete. Phylogenomic analysis revealed 597 bacterial and 171 archaeal MAGs, of which nearly all were distantly related to known cultivated isolates. In the 768 MAGs, the abundant Bacteria in phylum level included Proteobacteria, Desulfobacterota, Bacteroidota, Patescibacteria and Chloroflexota, while the abundant Archaea included Asgardarchaeota, Thermoplasmatota, and Thermoproteota. These results provide a dataset available for further interrogation of deep-sea microbial ecology.

Measurement(s)	metagenome assembled genomes
Technology Type(s)	metagenome sequencing and genome binning
Sample Characteristic - Organism	microorganism
Sample Characteristic - Environment	marine cold seep biome
Sample Characteristic - Location	South China Sea

Characteristics of nitrogen deposition research within grassland ecosystems globally and its insight from grassland microbial community changes in China

As global change continues to intensify, the mode and rate of nitrogen input from the atmosphere to grassland ecosystems had changed dramatically. Firstly, we conducted a systematic analysis of the literature on the topic of nitrogen deposition impacts over the past 30 years using a bibliometric analysis. A systematic review of the global research status, publication patterns, research hotspots and important literature. We found a large number of publications in the Chinese region, and mainly focuses on the field of microorganisms. Secondly, we used a meta-analysis to focus on microbial changes using the Chinese grassland ecosystem as an example. The results show that the research on nitrogen deposition in grassland ecosystems shows an exponential development trend, and the authors and research institutions of the publications are mainly concentrated in China, North America, and Western Europe. The keyword clustering results showed 11 important themes labeled climate change, elevated CO₂, species richness and diversity, etc. in these studies. The burst keyword analysis indicated that temperature sensitivity, microbial communities, etc. are the key research directions. The results of the meta-analysis found that nitrogen addition decreased soil microbial diversity, and different ecosystems may respond differently. Treatment time, nitrogen addition rate, external environmental conditions, and pH had major effects on microbial alpha diversity and biomass. The loss of microbial diversity and the reduction of biomass with nitrogen fertilizer addition will alter ecosystem functioning, with dramatic impacts on global climate change. The results of the study will help researchers to further understand the subject and have a deep understanding of research hotspots, which are of great value to future scientific research.

Quantitative microbial population study reveals geographical differences in bacterial symbionts of Ixodes ricinus

BACKGROUND

Ixodes ricinus ticks vector pathogens that cause serious health concerns. Like in other arthropods, the microbiome may affect the tick's biology, with consequences for pathogen transmission. Here, we explored the bacterial communities of I. ricinus across its developmental stages and six geographic locations by the 16S rRNA amplicon sequencing, combined with quantification of the bacterial load.

RESULTS

A wide range of bacterial loads was found. Accurate quantification of low microbial biomass samples permitted comparisons to high biomass samples, despite the presence of contaminating DNA. The bacterial communities of ticks were associated with geographical location rather than life stage, and differences in Rickettsia abundance determined this association. Subsequently, we explored the geographical distribution of four vertically transmitted symbionts identified in the microbiome analysis. For that, we screened 16,555 nymphs from 19 forest sites for R. helvetica, Rickettsiella spp., Midichloria mitochondrii, and Spiroplasma ixodetis. Also, the infection rates and distributions of these symbionts were compared to the horizontally transmitted pathogens Borrelia burgdorferi sensu lato, Anaplasma phagocytophilum, and Neoehrlichia mikurensis. The infection rates of all vertically transmitted symbionts differed between the study sites, and none of the symbionts was present in all tested ticks suggesting a facultative association with I. ricinus. The proportions in which symbionts occurred in populations of I. ricinus were highly variable, but geographically close study sites expressed similar proportions. These patterns were in contrast to what we observed for horizontally transmitted pathogens. Lastly, nearly 12% of tested nymphs were free of any targeted microorganisms, which is in line with the microbiome analyses.

CONCLUSIONS

Our results show that the microbiome of I. ricinus is highly variable, but changes gradually and ticks originating from geographically close forest sites express similar bacterial communities. This suggests that geography-related factors affect the infection rates of vertically transmitted symbionts in I. ricinus. Since some symbionts, such as R. helvetica can cause disease in humans, we propose that public health investigations consider geographical differences in its infection rates.

A rarefaction-without-resampling extension of PERMANOVA for testing presence-absence associations in the microbiome

MOTIVATION

PERMANOVA is currently the most commonly used method for testing community-level hypotheses about microbiome associations with covariates of interest. PERMANOVA can test for associations that result from changes in which taxa are present or absent by using the Jaccard or unweighted UniFrac distance. However, such presence-absence analyses face a unique challenge: confounding by library size (total sample read count), which occurs when library size is associated with covariates in the analysis. It is known that rarefaction (subsampling to a common library size) controls this bias but at the potential costs of information loss and the introduction of a stochastic component into the analysis.

RESULTS

Here, we develop a non-stochastic approach to PERMANOVA presence-absence analyses that aggregates information over all potential rarefaction replicates without actual resampling, when the Jaccard or unweighted UniFrac distance is used. We compare this new approach to three possible ways of aggregating PERMANOVA over multiple rarefactions obtained from resampling: averaging the distance matrix, averaging the (element-wise) squared distance matrix and averaging the F-statistic. Our simulations indicate that our non-stochastic approach is robust to confounding by library size and outperforms each of the stochastic resampling approaches. We also show that, when overdispersion is low, averaging the (element-wise) squared distance outperforms averaging the unsquared distance, currently implemented in the R package vegan. We illustrate our methods using an analysis of data on inflammatory bowel disease in which samples from case participants have systematically smaller library sizes than samples from control participants.

AVAILABILITY AND IMPLEMENTATION

We have implemented all the approaches described above, including the function for calculating the analytical average of the squared or unsquared distance matrix, in our R package LDM, which is available on GitHub at https://github.com/yijuanhu/LDM.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Characterization of Vaginal Microbiota in Third Trimester Premature Rupture of Membranes Patients through 16S rDNA Sequencing

In China, premature rupture of membranes (PROM) counts as a major pregnancy complication in China and usually results into adverse pregnancy outcomes. We analysed the vagina microbiome composition using 16S rDNA V3−V4 amplicon sequencing technology, in this prospective study of 441 women in their third trimester of pregnancy. We first divided all subjects into PROM and HC (healthy control) groups, in order to investigate the correlation of vagina microbiome composition and the development of PROM. We found that seven pathogens were higher in the PROM group as compared to the HC group with statistical significance. We also split all subjects into three groups based on Lactobacillus abundance-dominant (Lactobacillus > 90%), intermediate (Lactobacillus 30−90%) and depleted (Lactobacillus < 30%) groups, and explored nine pathogenic genera that were higher in the depleted group than the intermediate and dominant groups having statistical significance. Finally, using integrated analysis and logistics regression modelling, we discovered that Lactobacillus (coeff = −0.09, p = 0.04) was linked to the decreased risk of PROM, while Gardnerella (coeff = 0.04, p = 0.02), Prevotella (coeff = 0.11, p = 0.02), Megasphaera (coeff = 0.04, p = 0.01), Ureaplasma (coeff = 0.004, p = 0.01) and Dialister (coeff = 0.001, p = 0.04) were associated with the increased risk of PROM. Further study on how these pathogens interact with vaginal microbiota and the host would result in a better understanding of PROM development.

A metagenomic DNA sequencing assay that is robust against environmental DNA contamination

Metagenomic DNA sequencing is a powerful tool to characterize microbial communities but is sensitive to environmental DNA contamination, in particular when applied to samples with low microbial biomass. Here, we present Sample-Intrinsic microbial DNA Found by Tagging and sequencing (SIFT-seq) a metagenomic sequencing assay that is robust against environmental DNA contamination introduced during sample preparation. The core idea of SIFT-seq is to tag the DNA in the sample prior to DNA isolation and library preparation with a label that can be recorded by DNA sequencing. Any contaminating DNA that is introduced in the sample after tagging can then be bioinformatically identified and removed. We applied SIFT-seq to screen for infections from microorganisms with low burden in blood and urine, to identify COVID-19 co-infection, to characterize the urinary microbiome, and to identify microbial DNA signatures of sepsis and inflammatory bowel disease in blood.

Tardigrade Community Microbiomes in North American Orchards Include Putative Endosymbionts and Plant Pathogens

The microbiome of tardigrades, a phylum of microscopic animals best known for their ability to survive extreme conditions, is poorly studied worldwide and completely unknown in North America. An improved understanding of tardigrade-associated bacteria is particularly important because tardigrades have been shown to act as vectors of the plant pathogen Xanthomonas campestris in the laboratory. However, the potential role of tardigrades as reservoirs and vectors of phytopathogens has not been investigated further. This study analyzed the microbiota of tardigrades from six apple orchards in central Iowa, United States, and is the first analysis of the microbiota of North American tardigrades. It is also the first ever study of the tardigrade microbiome in an agricultural setting. We utilized 16S rRNA gene amplicon sequencing to characterize the tardigrade community microbiome across four contrasts: location, substrate type (moss or lichen), collection year, and tardigrades vs. their substrate. Alpha diversity of the tardigrade community microbiome differed significantly by location and year of collection but not by substrate type. Our work also corroborated earlier findings, demonstrating that tardigrades harbor a distinct microbiota from their environment. We also identified tardigrade-associated taxa that belong to genera known to contain phytopathogens (Pseudomonas, Ralstonia, and the Pantoea/Erwinia complex). Finally, we observed members of the genera Rickettsia and Wolbachia in the tardigrade microbiome; because these are obligate intracellular genera, we consider these taxa to be putative endosymbionts of tardigrades. These results suggest the presence of putative endosymbionts and phytopathogens in the microbiota of wild tardigrades in North America.

Cancer type classification using plasma cell-free RNAs derived from human and microbes

The utility of cell-free nucleic acids in monitoring cancer has been recognized by both scientists and clinicians. In addition to human transcripts, a fraction of cell-free nucleic acids in human plasma were proven to be derived from microbes and reported to have relevance to cancer. To obtain a better understanding of plasma cell-free RNAs (cfRNAs) in cancer patients, we profiled cfRNAs in ~300 plasma samples of 5 cancer types (colorectal cancer, stomach cancer, liver cancer, lung cancer, and esophageal cancer) and healthy donors (HDs) with RNA-seq. Microbe-derived cfRNAs were consistently detected by different computational methods when potential contaminations were carefully filtered. Clinically relevant signals were identified from human and microbial reads, and enriched Kyoto Encyclopedia of Genes and Genomes pathways of downregulated human genes and higher prevalence torque teno viruses both suggest that a fraction of cancer patients were immunosuppressed. Our data support the diagnostic value of human and microbe-derived plasma cfRNAs for cancer detection, as an area under the ROC curve of approximately 0.9 for distinguishing cancer patients from HDs was achieved. Moreover, human and microbial cfRNAs both have cancer type specificity, and combining two types of features could distinguish tumors of five different primary locations with an average recall of 60.4%. Compared to using human features alone, adding microbial features improved the average recall by approximately 8%. In summary, this work provides evidence for the clinical relevance of human and microbe-derived plasma cfRNAs and their potential utilities in cancer detection as well as the determination of tumor sites.

Microbiota in Tumors: From Understanding to Application

Microbes with complex functions have been found to be a potential component in tumor microenvironments. Due to their low biomass and other obstacles, intratumor microbiota is poorly understood. Mucosal sites and normal adjacent tissues are important sources of intratumor microbiota, while hematogenous spread also leads to the invasion of microbes. Intratumor microbiota affects the progression of tumors through several mechanisms, such as DNA damage, activation of oncogenic pathways, induction of immunosuppression, and metabolization of drugs. Notably, in different types of tumors, the composition and abundance of intratumor microbiota are highly heterogeneous and may play different roles in the progression of tumors. Because of the concern in this field, several techniques such as omics and immunological methods have been used to study intratumor microbiota. Here, recent progress in this field is reviewed, including the potential sources of intratumor microbiota, their functions and related mechanisms, and their heterogeneity. Techniques that can be used to study intratumor microbiota are also discussed. Moreover, research is summarized into the development of strategies that can be used in antitumor treatment and prospects for possible future research in this field.

Injection site microflora in persons with diabetes: why needle reuse is not associated with increased infections?

Needle reuse is a common practice and primary cause of customer compliance issues such as pain, bruising, clogging, injection site reactions (ISR), and associated lipodystrophy. This study aimed to characterize skin microflora at injection sites and establish microbial contamination of used pen injectors and needles. The second objective was to evaluate the risk of infections during typical and repeated subcutaneous injections. 50 participants with diabetes and 50 controls (n = 100) were sampled through tape strips and skin swabs on the abdomen and thigh for skin microflora. Used pen injectors and needles were collected after in‐home use and from the hospital after drug administration by health care professionals (HCPs). Samples were analyzed by conventional culture, matrix‐assisted laser desorption/ionization‐time of flight (MALDI‐TOF), mass spectrometry (MS), confocal laser scanning microscopy (CLSM), and 16S/ITS high throughput sequencing (HTS). A mathematical model simulated the risk of needle contamination during injections. Injection site populations were in 10² cells/cm² order, with increased viable bacteria and anaerobic bacteria on the skin in persons with diabetes (p = 0.05). Interpersonal variation dominated other factors such as sex or location. A higher prevalence of Staphylococcus aureus on abdominal skin was found in persons with diabetes than control skin (p ≤ 0.05). Most needles and cartridges (95% and 86%) contained no biological signal. The location of the device collection (hospital vs home‐use) and use regimen did not affect contamination. CLSM revealed scarcely populated skin microflora scattered in aggregates, diplo, or single cells. Our mathematical model demonstrated that penetrating bacteria colonies during subcutaneous injection is unlikely. These findings clarify the lack of documented skin infections from subcutaneous insulin injections in research. Furthermore, these results can motivate the innovation and development of durable, reusable injection systems with pharmacoeconomic value and a simplified and enhanced user experience for patients.

Metagenomics Approaches to Investigate the Neonatal Gut Microbiome

Early infancy is critical for the development of an infant's gut flora. Many factors can influence microbiota development during the pre- and postnatal periods, including maternal factors, antibiotic exposure, mode of delivery, dietary patterns, and feeding type. Therefore, investigating the connection between these variables and host and microbiome interactions in neonatal development would be of great interest. As the "unculturable" era of microbiome research gives way to an intrinsically multidisciplinary field, microbiome research has reaped the advantages of technological advancements in next-generation sequencing, particularly 16S rRNA gene amplicon and shotgun sequencing, which have considerably expanded our knowledge about gut microbiota development during early life. Using omics approaches to explore the neonatal microbiome may help to better understand the link between the microbiome and newborn diseases. Herein, we summarized the metagenomics methods and tools used to advance knowledge on the neonatal microbiome origin and evolution and how the microbiome shapes early and late individuals' lives for health and disease. The way to overcome limitations in neonatal microbiome studies will be discussed.

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.