Understanding and overcoming the pitfalls and biases of next-generation sequencing (NGS) methods for use in the routine clinical microbiological diagnostic laboratory

Monitoring Bacterial Community Dynamics in a Drinking Water Treatment Plant: An Integrative Approach Using Metabarcoding and Microbial Indicators in Large Water Volumes

Monitoring bacterial communities in a drinking water treatment plant (DWTP) may help to understand their regular operations. Bacterial community dynamics in an advanced full-scale DWTP were analyzed by 16S rRNA metabarcoding, and microbial water quality indicators were determined at nine different stages of potabilization: river water and groundwater intake, decantation, sand filtration, ozonization, carbon filtration, reverse osmosis, mixing chamber and post-chlorination drinking water. The microbial content of large water volumes (up to 1100 L) was concentrated by hollow fiber ultrafiltration. Around 10 million reads were obtained and grouped into 10,039 amplicon sequence variants. Metabarcoding analysis showed high bacterial diversity at all treatment stages and above all in groundwater intake, followed by carbon filtration and mixing chamber samples. Shifts in bacterial communities occurred downstream of ozonization, carbon filtration, and, more drastically, chlorination. Proteobacteria and Bacteroidota predominated in river water and throughout the process, but in the final drinking water, the strong selective pressure of chlorination reduced diversity and was clearly dominated by Cyanobacteria. Significant seasonal variation in species distribution was observed in decantation and carbon filtration samples. Some amplicon sequence variants related to potentially pathogenic genera were found in the DWTP. However, they were either not detected in the final water or in very low abundance (<2%), and all EU Directive quality standards were fully met. A combination of culture and high-throughput sequencing techniques may help DWTP managers to detect shifts in microbiome, allowing for a more in-depth assessment of operational performance.

Prospective Comparison Between Shotgun Metagenomics and Sanger Sequencing of the 16S rRNA Gene for the Etiological Diagnosis of Infections

Bacteriological diagnosis is traditionally based on culture. However, this method may be limited by the difficulty of cultivating certain species or by prior exposure to antibiotics, which justifies the resort to molecular methods, such as Sanger sequencing of the 16S rRNA gene (Sanger 16S). Recently, shotgun metagenomics (SMg) has emerged as a powerful tool to identify a wide range of pathogenic microorganisms in numerous clinical contexts. In this study, we compared the performance of SMg to Sanger 16S for bacterial detection and identification. All patients’ samples for which Sanger 16S was requested between November 2019 and April 2020 in our institution were prospectively included. The corresponding samples were tested with a commercial 16S semi-automated method and a semi-quantitative pan-microorganism DNA- and RNA-based SMg method. Sixty-seven samples from 64 patients were analyzed. Overall, SMg was able to identify a bacterial etiology in 46.3% of cases (31/67) vs. 38.8% (26/67) with Sanger 16S. This difference reached significance when only the results obtained at the species level were compared (28/67 vs. 13/67). This study provides one of the first evidence of a significantly better performance of SMg than Sanger 16S for bacterial detection at the species level in patients with infectious diseases for whom culture-based methods have failed. This technology has the potential to replace Sanger 16S in routine practice for infectious disease diagnosis.

Raman Spectroscopy-A Novel Method for Identification and Characterization of Microbes on a Single-Cell Level in Clinical Settings

Rapid and accurate identification of pathogens causing infections is one of the biggest challenges in medicine. Timely identification of causative agents and their antimicrobial resistance profile can significantly improve the management of infection, lower costs for healthcare, mitigate ever-growing antimicrobial resistance and in many cases, save lives. Raman spectroscopy was shown to be a useful-quick, non-invasive, and non-destructive -tool for identifying microbes from solid and liquid media. Modifications of Raman spectroscopy and/or pretreatment of samples allow single-cell analyses and identification of microbes from various samples. It was shown that those non-culture-based approaches could also detect antimicrobial resistance. Moreover, recent studies suggest that a combination of Raman spectroscopy with optical tweezers has the potential to identify microbes directly from human body fluids. This review aims to summarize recent advances in non-culture-based approaches of identification of microbes and their virulence factors, including antimicrobial resistance, using methods based on Raman spectroscopy in the context of possible use in the future point-of-care diagnostic process.

Best Practices for Probiotic Research in Athletic and Physically Active Populations: Guidance for Future Randomized Controlled Trials

Probiotic supplementation, traditionally used for the prevention or treatment of a variety of disease indications, is now recognized in a variety of population groups including athletes and those physically active for improving general health and performance. However, experimental and clinical trials with probiotics commonly suffer from design flaws and different outcome measures, making comparison and synthesis of conclusions difficult. Here we review current randomized controlled trials (RCTs) using probiotics for performance improvement, prevention of common illnesses, or general health, in a specific target population (athletes and those physically active). Future RCTs should address the key elements of (1) properly defining and characterizing a probiotic intervention, (2) study design factors, (3) study population characteristics, and (4) outcome measures, that will allow valid conclusions to be drawn. Careful evaluation and implementation of these elements should yield improved trials, which will better facilitate the generation of evidence-based probiotic supplementation recommendations for athletes and physically active individuals.

Maternal anthropometric variables and clinical factors shape neonatal microbiome

Recent studies indicate the existence of a complex microbiome in the meconium of newborns that plays a key role in regulating many host health-related conditions. However, a high variability between studies has been observed so far. In the present study, the meconium microbiome composition and the predicted microbial metabolic pathways were analysed in a consecutive cohort of 96 full-term newborns. The effect of maternal epidemiological variables on meconium diversity was analysed using regression analysis and PERMANOVA. Meconium microbiome composition mainly included Proteobacteria (30.95%), Bacteroidetes (23.17%) and Firmicutes (17.13%), while for predicted metabolic pathways, the most abundant genes belonged to the class “metabolism”. We observed a significant effect of maternal Rh factor on Shannon and Inverse Simpson indexes (p = 0.045 and p = 0.049 respectively) and a significant effect of delivery mode and maternal antibiotic exposure on Jaccard and Bray–Curtis dissimilarities (p = 0.001 and 0.002 respectively), while gestational age was associated with observed richness and Shannon indexes (p = 0.018 and 0.037 respectively), and Jaccard and Bray–Curtis dissimilarities (p = 0.014 and 0.013 respectively). The association involving maternal Rh phenotype suggests a role for host genetics in shaping meconium microbiome prior to the exposition to the most well-known environmental variables, which will influence microbiome maturation in the newborn.

High-throughput qPCR and 16S rRNA gene amplicon sequencing as complementary methods for the investigation of the cheese microbiota

Background

Next-generation sequencing (NGS) methods and especially 16S rRNA gene amplicon sequencing have become indispensable tools in microbial ecology. While they have opened up new possibilities for studying microbial communities, they also have one drawback, namely providing only relative abundances and thus compositional data. Quantitative PCR (qPCR) has been used for years for the quantification of bacteria. However, this method requires the development of specific primers and has a low throughput. The constraint of low throughput has recently been overcome by the development of high-throughput qPCR (HT-qPCR), which allows for the simultaneous detection of the most prevalent bacteria in moderately complex systems, such as cheese and other fermented dairy foods. In the present study, the performance of the two approaches, NGS and HT-qPCR, was compared by analyzing the same DNA samples from 21 Raclette du Valais protected designation of origin (PDO) cheeses. Based on the results obtained, the differences, accuracy, and usefulness of the two approaches were studied in detail.

Results

The results obtained using NGS (non-targeted) and HT-qPCR (targeted) show considerable agreement in determining the microbial composition of the cheese DNA samples studied, albeit the fundamentally different nature of these two approaches. A few inconsistencies in species detection were observed, particularly for less abundant ones. The detailed comparison of the results for 15 bacterial species/groups measured by both methods revealed a considerable bias for certain bacterial species in the measurements of the amplicon sequencing approach. We identified as probable origin to this PCR bias due to primer mismatches, variations in the number of copies for the 16S rRNA gene, and bias introduced in the bioinformatics analysis.

Conclusion

As the normalized microbial composition results of NGS and HT-qPCR agreed for most of the 21 cheese samples analyzed, both methods can be considered as complementary and reliable for studying the microbial composition of cheese. Their combined application proved to be very helpful in identifying potential biases and overcoming methodological limitations in the quantitative analysis of the cheese microbiota.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12866-022-02451-y.

Sequence meets function-microbiota and cardiovascular disease

The discovery that gut-microbiota plays a profound role in human health has opened a new avenue of basic and clinical research. Application of ecological approaches where the bacterial 16S rRNA gene is queried has provided a number of candidate bacteria associated with coronary artery disease and hypertension. We examine the associations between gut microbiota and a variety of cardiovascular disease (CVD) including atherosclerosis, coronary artery disease, and blood pressure. These approaches are associative in nature and there is now increasing interest in identifying the mechanisms underlying these associations. We discuss three potential mechanisms including: gut permeability and endotoxemia, increased immune system activation, and microbial derived metabolites. In addition to discussing these potential mechanisms we highlight current studies manipulating the gut microbiota or microbial metabolites to move beyond sequence-based association studies. The goal of these mechanistic studies is to determine the mode of action by which the gut microbiota may affect disease susceptibility and severity. Importantly, the gut microbiota appears to have a significant effect on host metabolism and CVD by producing metabolites entering the host circulatory system such as short-chain fatty acids and trimethylamine N-Oxide. Therefore, the intersection of metabolomics and microbiota research may yield novel targets to reduce disease susceptibility. Finally, we discuss approaches to demonstrate causality such as specific diet changes, inhibition of microbial pathways, and fecal microbiota transplant.

Detection of Nocardia by 16S Ribosomal RNA Gene PCR and Metagenomic Next-Generation Sequencing (mNGS)

In this study, the aim was to investigate the discriminatory power of molecular diagnostics based on mNGS and traditional 16S ribosomal RNA PCR among Nocardia species. A total of fourteen clinical isolates from patients with positive Nocardia cultures and clinical evidence were included between January 2017 and June 2020 in HeNan Provincial People’s Hospital. DNA extraction and 16S rRNA PCR were performed on positive cultures, and pathogens were detected by mNGS in these same samples directly. Among the 14 Nocardia isolates, four species were identified, and N. cyriacigeorgica (8 cases) is the most common species. Twelve of the 14 Nocardia spp. isolates were identified by the two methods, while two strains of N. cyriacigeorgica were not identified by mNGS. All tested isolates showed susceptibility to trimethoprim-sulfamethoxazole (SXT), amikacin and linezolid. Apart from Nocardia species, other pathogens such as Acinetobacter baumannii, Klebsiella pneumonia, Aspergillus, Enterococcus faecalis, Human herpesvirus, etc., were detected from the same clinical samples by mNGS. However, these different pathogens were considered as colonization or contamination. We found that it is essential to accurately identify species for determining antibiotic sensitivity and, consequently, choosing antibiotic treatment. 16S rRNA PCR was useful for identification of nocardial infection among species, while this technique needs the clinicians to make the pre-considerations of nocardiosis. However, mNGS may be a putative tool for rapid and accurate detection and identification of Nocardia, beneficial for applications of antimicrobial drugs and timely adjustments of medication.

Bovine respiratory microbiota of feedlot cattle and its association with disease

Bovine respiratory disease (BRD), as one of the most common and costly diseases in the beef cattle industry, has significant adverse impacts on global food security and the economic stability of the industry. The bovine respiratory microbiome is strongly associated with health and disease and may provide insights for alternative therapy when treating BRD. The niche-specific microbiome communities that colonize the inter-surface of the upper and the lower respiratory tract consist of a dynamic and complex ecological system. The correlation between the disequilibrium in the respiratory ecosystem and BRD has become a hot research topic. Hence, we summarize the pathogenesis and clinical signs of BRD and the alteration of the respiratory microbiota. Current research techniques and the biogeography of the microbiome in the healthy respiratory tract are also reviewed. We discuss the process of resident microbiota and pathogen colonization as well as the host immune response. Although associations between the microbiota and BRD have been revealed to some extent, interpreting the development of BRD in relation to respiratory microbial dysbiosis will likely be the direction for upcoming studies, which will allow us to better understand the importance of the airway microbiome and its contributions to animal health and performance.

What Does 16S rRNA Gene-Targeted Next Generation Sequencing Contribute to the Study of Infective Endocarditis in Heart-Valve Tissue?

Infective endocarditis (IE) is a severe and life-threatening disease. Identification of infectious etiology is essential for establishing the appropriate antimicrobial treatment and decreasing mortality. The aim of this study was to explore the potential utility of metataxonomics for improving microbiological diagnosis of IE. Here, next-generation sequencing (NGS) of the V3-V4 region of the 16S rRNA gene was performed in 27 heart valve tissues (18 natives, 5 intravascular devices, and 4 prosthetics) from 27 patients diagnosed with IE (4 of them with negative blood cultures). Metataxonomics matched with conventional diagnostic techniques in 24/27 cases (88.9%). The same bacterial family was assigned to 24 cases; the same genus, to 23 cases; and the same species, to 13 cases. In 22 of them, the etiological agent was represented by percentages > 99% of the reads and in two cases, by ~70%. Staphylococcus aureus was detected in a previously microbiological undiagnosed patient. Thus, microbiological diagnosis with 16S rRNA gene targeted-NGS was possible in one more sample than using traditional techniques. The remaining two patients showed no coincidence between traditional and 16S rRNA gene-targeted NGS microbiological diagnoses. In addition, 16S rRNA gene-targeted NGS allowed us to suggest coinfections that were supported by clinical data in one patient, and minority records also verified mixed infections in three cases. In our series, metataxonomics was valid for the identification of the causative agents, although more studies are needed before implementation of 16S rRNA gene-targeted NGS for the diagnosis of IE.

Diet and microbiome in the beginning of the sequence of gut inflammation

Inflammatory bowel disease (IBD) is a chronic inflammatory condition of the gastrointestinal tract due, at least partially, to an aberrant and excessive mucosal immune response to gut bacteria in genetically-predisposed individuals under certain environmental factors. The incidence of IBD is rising in western and newly industrialized countries, paralleling the increase of westernized dietary patterns, through new antigens, epithelial function and permeability, epigenetic mechanisms (e.g., DNA methylation), and alteration of the gut microbiome. Alteration in the composition and functionality of the gut microbiome (including bacteria, viruses and fungi) seems to be a nuclear pathogenic factor. The microbiome itself is dynamic, and the changes in food quality, dietary habits, living conditions and hygiene of these western societies, could interact in a complex manner as modulators of dysbiosis, thereby influencing the activation of immune cells' promoting inflammation. The microbiome produces diverse small molecules via several metabolic ways, with the fiber-derived short-chain fatty acids (i.e., butyrate) as main elements and having anti-inflammatory effects. These metabolites and some micronutrients of the diet (i.e., vitamins, folic acid, beta carotene and trace elements) are regulators of innate and adaptive intestinal immune homeostasis. An excessive and unhealthy consumption of sugar, animal fat and a low-vegetable and -fiber diet are risk factors for IBD appearance. Furthermore, metabolism of nutrients in intestinal epithelium and in gut microbiota is altered by inflammation, changing the demand for nutrients needed for homeostasis. This role of food and a reduced gut microbial diversity in causing IBD might also have a prophylactic or therapeutic role for IBD. The relationship between dietary intake, symptoms, and bowel inflammation could lead to dietary and lifestyle recommendations, including diets with abundant fruits, vegetables, olive oil and oily fish, which have anti-inflammatory effects and could prevent dysbiosis and IBD. Dietary modulation and appropriate exclusion diets might be a new complementary management for treatment at disease flares and in refractory patients, even reducing complications, hospitalizations and surgery, through modifying the luminal intestinal environment.

Bacterial keratitis: identifying the areas of clinical uncertainty

Bacterial keratitis is a common corneal infection that is treated with topical antimicrobials. By the time of presentation there may already be severe visual loss from corneal ulceration and opacity, which may persist despite treatment. There are significant differences in the associated risk factors and the bacterial isolates between high income and low- or middle-income countries, so that general management guidelines may not be appropriate. Although the diagnosis of bacterial keratitis may seem intuitive there are multiple uncertainties about the criteria that are used, which impacts the interpretation of investigations and recruitment to clinical studies. Importantly, the concept that bacterial keratitis can only be confirmed by culture ignores the approximately 50% of cases clinically consistent with bacterial keratitis in which investigations are negative. The aetiology of these culture-negative cases is unknown. Currently, the estimation of bacterial susceptibility to antimicrobials is based on data from systemic administration and achievable serum or tissue concentrations, rather than relevant corneal concentrations and biological activity in the cornea. The provision to the clinician of minimum inhibitory concentrations of the antimicrobials for the isolated bacteria would be an important step forward. An increase in the prevalence of antimicrobial resistance is a concern, but the effect this has on disease outcomes is yet unclear. Virulence factors are not routinely assessed although they may affect the pathogenicity of bacteria within species and affect outcomes. New technologies have been developed to detect and kill bacteria, and their application to bacterial keratitis is discussed. In this review we present the multiple areas of clinical uncertainty that hamper research and the clinical management of bacterial keratitis, and we address some of the assumptions and dogma that have become established in the literature.

Comparative meta-omics for identifying pathogens associated with prosthetic joint infection

Prosthetic joint infections (PJI) are economically and personally costly, and their incidence has been increasing in the United States. Herein, we compared 16S rRNA amplicon sequencing (16S), shotgun metagenomics (MG) and metatranscriptomics (MT) in identifying pathogens causing PJI. Samples were collected from 30 patients, including 10 patients undergoing revision arthroplasty for infection, 10 patients receiving revision for aseptic failure, and 10 patients undergoing primary total joint arthroplasty. Synovial fluid and peripheral blood samples from the patients were obtained at time of surgery. Analysis revealed distinct microbial communities between primary, aseptic, and infected samples using MG, MT, (PERMANOVA p = 0.001), and 16S sequencing (PERMANOVA p < 0.01). MG and MT had higher concordance with culture (83%) compared to 0% concordance of 16S results. Supervised learning methods revealed MT datasets most clearly differentiated infected, primary, and aseptic sample groups. MT data also revealed more antibiotic resistance genes, with improved concordance results compared to MG. These data suggest that a differential and underlying microbial ecology exists within uninfected and infected joints. This study represents the first application of RNA-based sequencing (MT). Further work on larger cohorts will provide opportunities to employ deep learning approaches to improve accuracy, predictive power, and clinical utility.

Centennial Review: Factors affecting the chicken gastrointestinal microbial composition and their association with gut health and productive performance

Maintenance of "gut health" is considered a priority in commercial chicken farms, although a precise definition of what constitutes gut health and how to evaluate it is still lacking. In research settings, monitoring of gut microbiota has gained great attention as shifts in microbial community composition have been associated with gut health and productive performance. However, microbial signatures associated with productivity remain elusive because of the high variability of the microbiota of individual birds resulting in multiple and sometimes contradictory profiles associated with poor or high performance. The high costs associated with the testing and the need for the terminal sampling of a large number of birds for the collection of gut contents also make this tool of limited use in commercial settings. This review highlights the existing literature on the chicken digestive system and associated microbiota; factors affecting the gut microbiota and emergence of the major chicken enteric diseases coccidiosis and necrotic enteritis; methods to evaluate gut health and their association with performance; main issues in investigating chicken microbial populations; and the relationship of microbial profiles and production outcomes. Emphasis is given to emerging noninvasive and easy-to-collect sampling methods that could be used to monitor gut health and microbiological changes in commercial flocks.

Laboratory diagnosis of bacterial meningitis by direct detection, serotyping and Next Generation Sequencing: How 10 years of testing in New York State has evolved to improve laboratory diagnosis and public health

Since 2005, the Wadsworth Center (WC) has provided molecular testing on cerebrospinal fluid (CSF) and whole blood specimens in close collaboration with epidemiologists in New York State and New York City. In this study, we analyzed 10 years of data to demonstrate the significant value of utilizing molecular methods to assess patient specimens for etiologic agents of bacterial meningitis. A comprehensive molecular testing algorithm to detect and serotype/serogroup bacterial agents known to cause bacterial meningitis (Neisseria meningitidis, Streptococcus pneumoniae, Haemophilus influenzae and Streptococcus agalactiae) has evolved, and retrospective specimen testing has been essential for each improvement. Over a ten-year span from 2010 to 2019 the WC received 831 specimens from 634 patients with suspected bacterial meningitis. Real-time PCR was positive for at least one of the agents in 223 (27%) specimens from 183 patients (29%). Of the 223 positives, 146 (66%) were further characterized by real-time PCR into serogroup/serotype. Additionally, examination of 131 paired specimens of CSF and whole blood from the same patients found better detection in CSF, but whole blood is a useful alternative for diagnosis when CSF is not available. For specimens initially PCR-negative, 16S rDNA Sanger sequencing was requested by the submitter for 146 cases resulting in the identification of bacterial agents in an additional 24 (16%) specimens. In a retrospective study, Next Generation Sequencing (NGS) was evaluated for the detection of pathogens in 53 previously tested PCR-negative CSF specimens and identified bacteria in 14 (26%) specimens. This molecular testing algorithm has provided clinicians a diagnosis when culture is negative with the potential to guide therapy. It has also aided public health in determining when antibiotic prophylaxis was needed, augmented surveillance data to yield a fuller picture of community prevalence, and highlighted gaps in the spectrum of agents that cause bacterial meningitis.

Whole Genome Sequencing Provides an Added Value to the Investigation of Staphylococcal Food Poisoning Outbreaks

Through staphylococcal enterotoxin (SE) production, Staphylococcus aureus is a common cause of food poisoning. Detection of staphylococcal food poisoning (SFP) is mostly performed using immunoassays, which, however, only detect five of 27 SEs described to date. Polymerase chain reactions are, therefore, frequently used in complement to identify a bigger arsenal of SE at the gene level (se) but are labor-intensive. Complete se profiling of isolates from different sources, i.e., food and human cases, is, however, important to provide an indication of their potential link within foodborne outbreak investigation. In addition to complete se gene profiling, relatedness between isolates is determined with more certainty using pulsed-field gel electrophoresis, Staphylococcus protein A gene typing and other methods, but these are shown to lack resolution. We evaluated how whole genome sequencing (WGS) can offer a solution to these shortcomings. By WGS analysis of a selection of S. aureus isolates, including some belonging to a confirmed foodborne outbreak, its added value as the ultimate multiplexing method was demonstrated. In contrast to PCR-based se gene detection for which primers are sometimes shown to be non-specific, WGS enabled complete se gene profiling with high performance, provided that a database containing reference sequences for all se genes was constructed and employed. The custom compiled database and applied parameters were made publicly available in an online user-friendly interface. As an all-in-one approach with high resolution, WGS additionally allowed inferring correct isolate relationships. The different DNA extraction kits that were tested affected neither se gene profiling nor relatedness determination, which is interesting for data sharing during SFP outbreak investigation. Although confirming the production of enterotoxins remains important for SFP investigation, we delivered a proof-of-concept that WGS is a valid alternative and/or complementary tool for outbreak investigation.

Contamination Issue in Viral Metagenomics: Problems, Solutions, and Clinical Perspectives

We describe the most common internal and external sources and types of contamination encountered in viral metagenomic studies and discuss their negative impact on sequencing results, particularly for low-biomass samples and clinical applications. We also propose some basic recommendations for reducing the background noise in viral shotgun metagenomic (SM) studies, which would limit the bias introduced by various classes of contaminants. Regardless of the specific viral SM protocol, contamination cannot be totally avoided; in particular, the issue of reagent contamination should always be addressed with high priority. There is an urgent need for the development and validation of standards for viral metagenomic studies especially if viral SM protocols will be more widely applied in diagnostics.

Comparison of 16S rRNA Gene Based Microbial Profiling Using Five Next-Generation Sequencers and Various Primers

Microbial community analysis based on the 16S rRNA-gene is used to investigate both beneficial and harmful microorganisms in various fields and environments. Recently, the next-generation sequencing (NGS) technology has enabled rapid and accurate microbial community analysis. Despite these advantages of NGS based metagenomics study, sample transport, storage conditions, amplification, library preparation kits, sequencing, and bioinformatics procedures can bias microbial community analysis results. In this study, eight mock communities were pooled from genomic DNA of Lactobacillus acidophilus KCTC 3164^T, Limosilactobacillus fermentum KCTC 3112^T, Lactobacillus gasseri KCTC 3163^T, Lacticaseibacillus paracasei subsp. paracasei KCTC 3510^T, Limosilactobacillus reuteri KCTC 3594^T, Lactococcus lactis subsp. lactis KCTC 3769^T, Bifidobacterium animalis subsp. lactis KCTC 5854^T, and Bifidobacterium breve KCTC 3220^T. The genomic DNAs were quantified by droplet digital PCR (ddPCR) and were mixed as mock communities. The mock communities were amplified with various 16S rRNA gene universal primer pairs and sequenced by MiSeq, IonTorrent, MGIseq-2000, Sequel II, and MinION NGS platforms. In a comparison of primer-dependent bias, the microbial profiles of V1-V2 and V3 regions were similar to the original ratio of the mock communities, while the microbial profiles of the V1-V3 region were relatively biased. In a comparison of platform-dependent bias, the sequence read from short-read platforms (MiSeq, IonTorrent, and MGIseq-2000) showed lower bias than that of long-read platforms (Sequel II and MinION). Meanwhile, the sequences read from Sequel II and MinION platforms were relatively biased in some mock communities. In the data of all NGS platforms and regions, L. acidophilus was greatly underrepresented while Lactococcus lactis subsp. lactis was generally overrepresented. In all samples of this study, the bias index (BI) was calculated and PCA was performed for comparison. The samples with biased relative abundance showed high BI values and were separated in the PCA results. In particular, analysis of regions rich in AT and GC poses problems for genome assembly, which can lead to sequencing bias. According to this comparative analysis, the development of reference material (RM) material has been proposed to calibrate the bias in microbiome analysis.

Streptococcus vaginalis sp. nov., a novel bacterial species isolated from vaginal swabs of a pregnant woman with diabetes

Sequences targeted at the V3 and V4 16S rRNA hypervariable regions of a streptococcal strain (P1L01^T) isolated from vaginal swabs of a pregnant woman with diabetes were 100% similar to those of Streptococcus anginosus subsp. whileyi. However, phylogenetic analysis based on 16S rRNA full-gene sequencing (1562 bp) revealed highest sequence similarity to Streptococcus periodonticum (98.7%), followed by Streptococcus anginosus subsp. whileyi (98.7%), and Streptococcus anginosus subsp. anginosus (98.4%). Phylogenies of housekeeping genes rpoB and groEL were compared to improve classification, and the results showed a clear separation between strain P1L01^T and closely related Streptococcus type strains. The complete genome of strain P1L01^T consisted of 2,108,769 bp with a G + C content of 38.5 mol%. Average nucleotide identity values, based on genome sequencing, between strain P1L01^T and Streptococcus periodonticum KCOM 2412^T, Streptococcus anginosus subsp. whileyi CCUG 39159^T, and Streptococcus anginosus subsp. anginosus NCTC 10713^T were 95.5%, 94.3%, and 95.3%, respectively. The highest in silico DNA-DNA hybridization value with respect to the closest species was 66.2%, i.e., below the species cutoff of 70% hybridization. The main cellular fatty acids of strain P1L01^T were 16:0, 18:1ω7c, and 14:0. On the basis of phylogenetic, genotypic and phenotypic data, we propose to classify this isolate as representative of a novel species of the genus Streptococcus, Streptococcus vaginalis sp. nov., in reference to its isolation from vaginal swabs, with strain P1L01^T (= NBRC 114754^T = BCRC 81289^T) as the type strain.

Utilizing the VirIdAl Pipeline to Search for Viruses in the Metagenomic Data of Bat Samples

According to various estimates, only a small percentage of existing viruses have been discovered, naturally much less being represented in the genomic databases. High-throughput sequencing technologies develop rapidly, empowering large-scale screening of various biological samples for the presence of pathogen-associated nucleotide sequences, but many organisms are yet to be attributed specific loci for identification. This problem particularly impedes viral screening, due to vast heterogeneity in viral genomes. In this paper, we present a new bioinformatic pipeline, VirIdAl, for detecting and identifying viral pathogens in sequencing data. We also demonstrate the utility of the new software by applying it to viral screening of the feces of bats collected in the Moscow region, which revealed a significant variety of viruses associated with bats, insects, plants, and protozoa. The presence of alpha and beta coronavirus reads, including the MERS-like bat virus, deserves a special mention, as it once again indicates that bats are indeed reservoirs for many viral pathogens. In addition, it was shown that alignment-based methods were unable to identify the taxon for a large proportion of reads, and we additionally applied other approaches, showing that they can further reveal the presence of viral agents in sequencing data. However, the incompleteness of viral databases remains a significant problem in the studies of viral diversity, and therefore necessitates the use of combined approaches, including those based on machine learning methods.

Metagenomic Next Generation Sequencing in the Detection of Pathogens in Cerebrospinal Fluid of Patients After Alternative Donor Transplantation: A Feasibility Analysis

Central nervous system (CNS) complications can occur in 9%–15% of patients after allogeneic hematopoietic stem cell transplantation (allo-HSCT). The clinical manifestations of the CNS complications are non-specific, with most of them being disturbances of consciousness, convulsions, headaches, fever, and epilepsy, making it difficult to infer the cause of the complications based on clinical manifestations. We retrospectively analyzed the sensitivity and feasibility of metagenomic next generation sequencing (mNGS) in the diagnosis of CNS infections after allo-HSCT. Lumbar punctures were performed on 20 patients with CNS symptoms after receiving alternative donor HSCT(AD-HSCT) at the Affiliated Cancer Hospital of Zhengzhou University from February 2019 to December 2020, and their cerebrospinal fluid (CSF) was collected. The mNGS technique was used to detect pathogens in the CSF. Routine CSF testing, biochemical analyses, G experiments, GM experiments, ink staining, acid-fast staining, and bacterial cultures were carried out, and quantitative PCR (qPCR) tests were used to detect cytomegalovirus (CMV), Epstein-Barr virus (EBV), BK polyomavirus (BKPyV), and human alphaherpesvirus (HHV). A total of 29 tests were performed with 21 of them being positive. Of the five negative patients, three were diagnosed with a posterior reversible encephalopathy syndrome, one as having transplantation-associated thrombotic microangiopathy, and one with transient seizure caused by hypertension. Fifteen patients tested positive, of which four had single infections and eleven had mixed infections. Five cases of fungal infections, six cases of bacterial infections, and 13 cases of viral infections were detected. Among the 13 cases of viral infections, ten cases were CMV(HHV-5); three were BKPyV; two were Torque teno virus (TTV); Two were HHV-1,two were EBV(HHV4), and one each of HpyV5 and HHV-6B. Thirteen patients tested positive for virus while the qPCR detection method of 6 identical specimens were below the minimum detection limit(<1×10³ U/ml). The mNGS technique is highly sensitive, and it can be used to diagnose CNS infections after allo-HSCT.

Gut microbiome and amyotrophic lateral sclerosis: A systematic review of current evidence

Amyotrophic lateral sclerosis (ALS), characterized by a loss of motor neurons in the brain and spinal cord, is a relatively rare but currently incurable neurodegenerative disease. The global incidence of ALS is estimated as 1.75 per 100,000 person-years and the global prevalence is estimated as 4.1-8.4 per 100,000 individuals. Contributions from outside the central nervous system to the etiology of ALS have been increasingly recognized. Gut microbiome is one of the most quickly growing fields of research for ALS. In this article, we performed a comprehensive review of the results from existing animal and human studies, to provide an up-to-date summary of the current research on gut microbiome and ALS. In brief, we found relatively consistent results from animal studies, suggesting an altered gut microbiome composition in experimental ALS. Publication bias might however be a concern. Findings from human studies are largely inconclusive. A few animal and human studies demonstrated the usefulness of intervention with microbial-derived metabolites in modulating the disease progression of ALS. We discussed potential methodological concerns in these studies, including study design, statistical power, handling process of biospecimens and sequencing data, as well as statistical methods and interpretation of results. Finally, we made a few proposals for continued microbiome research in ALS, with the aim to provide valid, reproducible, and translatable findings.

Potential biomarkers of infertility associated with microbiome imbalances

PROBLEM

The aim of this study was to investigate the possible relationship between vaginal/rectal microbiome disbalances and miRNA expression with infertility.

METHOD OF STUDY

Observational, exploratory, preliminary study. A total of 287 multiple IVF failure infertile patients were recruited. Twenty fertile women, not IVF failure, were recruited as the control group. Swab samples were collected from the vagina and rectum. Microbial composition by NGS and miRNA expression by real-time PCR of vaginal and rectal samples was measured. Immunometabolic markers from blood (insulin, vitamin D, LDL-cholesterol, ANA, TPO, Tg, and ASCA antibodies) and saliva (sIgA) were analyzed.

RESULT(S)

Infertile patients showed a lower bacterial richness and increased Firmicutes/Bacteroidetes ratio at rectal level and an increased Lactobacillus brevis/Lactobacillus iners ratio in vaginal samples regarding the fertile group. In the same rectal swab samples, we found that miR-21-5p, which is associated with tight junction disruption and yeast overgrowth, is upregulated and that miR-155-5p, which is associated with inflammation, is overexpressed in the unexplained infertile group (*p < .05). These deregulated miRNAs were also upregulated in the vaginal samples from the same patients (*p < .05).

CONCLUSION

miRNAs could be potential biomarkers of the inflammatory impact of microbiome disbalances in unexplained infertile women.

Sample Preparation and Diagnostic Methods for a Variety of Settings: A Comprehensive Review

Sample preparation is an essential step for nearly every type of biochemical analysis in use today. Among the most important of these analyses is the diagnosis of diseases, since their treatment may rely greatly on time and, in the case of infectious diseases, containing their spread within a population to prevent outbreaks. To address this, many different methods have been developed for use in the wide variety of settings for which they are needed. In this work, we have reviewed the literature and report on a broad range of methods that have been developed in recent years and their applications to point-of-care (POC), high-throughput screening, and low-resource and traditional clinical settings for diagnosis, including some of those that were developed in response to the coronavirus disease 2019 (COVID-19) pandemic. In addition to covering alternative approaches and improvements to traditional sample preparation techniques such as extractions and separations, techniques that have been developed with focuses on integration with smart devices, laboratory automation, and biosensors are also discussed.

Rapid and improved identification of drinking water bacteria using the Drinking Water Library, a dedicated MALDI-TOF MS database

According to the European Directives (UE) 2020/2184 and 2009/54/EC, which establishes the sanitary criteria for water intended for human consumption in Europe, water suitable for human consumption must be free of the bacterial indicators Escherichia coli, Clostridium perfringens and Enterococcus spp. Drinking water is also monitored for heterotrophic bacteria, which are not a human health risk, but can serve as an index of bacteriological water quality. Therefore, a rapid, accurate, and cost-effective method for the identification of these colonies would improve our understanding of the culturable bacteria of drinking water and facilitate the task of water management by treatment facilities. Matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) is potentially such a method, although most of the currently available mass spectral libraries have been developed in a clinical setting and have limited environmental applicability. In this work, a MALDI-TOF MS drinking water library (DWL) was defined and developed by targeting bacteria present in water intended for human consumption. This database, made up of 319 different bacterial strains, can contribute to the routine microbiological control of either treated drinking water or mineral bottled water carried out by water treatment and distribution operators, offering a faster identification rate compared to a clinical sample-based library. The DWL, made up of 96 bacterial genera, 44 of which are not represented in the MALDI-TOF MS bacterial Bruker Daltonics (BDAL) database, was found to significantly improve the identification of bacteria present in drinking water.

Healthcare-Associated Infections-Related Bacteriome and Antimicrobial Resistance Profiling: Assessing Contamination Hotspots in a Developing Country Public Hospital

Hospital-built environment colonization by healthcare-associated infections-related bacteria (HAIrB) and the interaction with their occupants have been studied to support more effective tools for HAI control. To investigate HAIrB dynamics and antimicrobial resistance (AMR) profile we carried out a 6-month surveillance program in a developing country public hospital, targeting patients, hospital environment, and healthcare workers, using culture-dependent and culture-independent 16S rRNA gene sequencing methods. The bacterial abundance in both approaches shows that the HAIrB group has important representativeness, with the taxa Enterobacteriaceae, Pseudomonas, Staphylococcus, E. coli, and A. baumannii widely dispersed and abundant over the time at the five different hospital units included in the survey. We observed a high abundance of HAIrB in the patient rectum, hands, and nasal sites. In the healthcare workers, the HAIrB distribution was similar for the hands, protective clothing, and mobile phones. In the hospital environment, the healthcare workers resting areas, bathrooms, and bed equipment presented a wide distribution of HAIrB and AMR, being classified as contamination hotspots. AMR is highest in patients, followed by the environment and healthcare workers. The most frequently detected beta-lactamases genes were, bla_SHV–like, bla_{OXA–23–like}, bla_{OXA–51–like}, bla_KPC–like, bla_CTX–M–1, bla_CTX–M–8, and bla_CTX–M–9 groups. Our results demonstrate that there is a wide spread of antimicrobial resistance due to HAIrB in the hospital environment, circulating among patients and healthcare workers. The contamination hotspots identified proved to be constant over time. In the fight for patient safety, these findings can reorient practices and help to set up new guidelines for HAI control.

Microbiome analysis, the immune response and transplantation in the era of next generation sequencing

The human gastrointestinal tract, skin and mucosal surfaces are inhabited by a complex system of bacteria, viruses, fungi, archaea, protists, and eukaryotic parasites with predominance of bacteria and bacterial viruses (bacteriophages). Collectively these microbes form the microbiota of the microecosystem of humans. Recent advancement in technologies for nucleic acid isolation from various environmental samples, feces and body secretions and advancements in shotgun throughput massive parallel DNA and RNA sequencing along with 16S ribosomal gene sequencing have unraveled the identity of otherwise unknown microbial entities constituting the human microecosystem. The improved transcriptome analysis, technological developments in biochemical analytical methods and availability of complex bioinformatics tools have allowed us to begin to understand the metabolome of the microbiome and the biochemical pathways and potential signal transduction pathways in human cells in response to microbial infections and their products. Also, developments in human whole genome sequencing, targeted gene sequencing of histocompatibility genes and other immune response associated genes by Next Generation Sequencing (NGS) have allowed us to have a better conceptualization of immune responses, and alloimmune responses. These modern technologies have enabled us to dive into the intricate relationship between commensal symbiotic and pathogenic microbiome and immune system. For the most part, the commensal symbiotic microbiota helps to maintain normal immune homeostasis besides providing healthy nutrients, facilitating digestion, and protecting the skin, mucosal and intestinal barriers. However, changes in diets, administration of therapeutic agents like antibiotics, chemotherapeutic agents, immunosuppressants etc. along with certain host factors including human histocompatibility antigens may alter the microbial ecosystem balance by causing changes in microbial constituents, hierarchy of microbial species and even dysbiosis. Such alterations may cause immune dysregulation, breach of barrier protection and lead to immunopathogenesis rather than immune homeostasis. The effects of human microbiome on immunity, health and disease are currently under intense research with cutting edge technologies in molecular biology, biochemistry, and bioinformatics along with tremendous ability to characterize immune response at single cell level. This review will discuss the contemporary status on human microbiome immune system interactions and their potential effects on health, immune homeostasis and allograft transplantation.

Is the skin microbiota a modifiable risk factor for breast disease?: A systematic review

PURPOSE

High prevalence, unreliable risk discrimination and poor clinical outcomes are observed in malignant and benign breast diseases (BD). The involvement of microbial communities in the development of BD has become topical, and distal influences of microbial dysregulation in the breast have been well established. Despite advances, the role of the breast skin microbiota in BD remains unclear. Interactions between the skin microbiota and the underlying mucosal immune system are complex. In homeostasis, the skin offers a physical barrier protecting underlying breast tissue from skin commensals and noxious environmental triggers. Our review aims to illuminate the role of the skin microbiota in the development of BD.

METHODS

Adhering to the PRISMA protocol, a systematic review was conducted utilising the Medline and Embase search engines.

RESULTS

Through a comprehensive search of the last ten years, twenty-two studies satisfied the inclusion criteria. Proteobacteria, Firmicutes, Actinobacteria and Bacteroidetes were identified as the most prevalent phyla of both breast tissue and skin in healthy controls and BD. High abundance of skin commensals, specifically some species of Staphylococcus, have been linked in breast cancer and metastases. Similarly, dysregulated microbial abundance is also seen in inflammatory and implant-associated BD. These findings raise the hypothesis that the skin microbiota plays a role in tissue homeostasis and may contribute to a range of breast pathologies. Several mechanisms of microbial transfer to underlying tissue have been proposed, including retrograde transfer through ductal systems, breakdown of the skin barrier, and migration through nipple-aspirate fluid.

CONCLUSION

Our review provides preliminary insights into the skin microbiota as a modifiable risk factor for BD. This raises opportunities for future studies in antimicrobials/probiotics as an adjunct to, or replacement of surgery; a diagnostic and/or prognostic tool for BD; and the possibility of conditioning the microbiota to manage BD.

Phospholipid fatty acid (PLFA) analysis as a tool to estimate absolute abundances from compositional 16S rRNA bacterial metabarcoding data

Microbial biodiversity monitoring through the analysis of DNA extracted from environmental samples is increasingly popular because it is perceived as being rapid, cost-effective, and flexible concerning the sample types studied. DNA can be extracted from diverse media before high-throughput sequencing of the prokaryotic 16S rRNA gene is used to characterize the taxonomic diversity and composition of the sample (known as metabarcoding). While sources of bias in metabarcoding methodologies are widely acknowledged, previous studies have focused mainly on the effects of these biases within a single substrate type, and relatively little is known of how these vary across substrates. We investigated the effect of substrate type (water, microbial mats, lake sediments, stream sediments, soil and a mock microbial community) on the relative performance of DNA metabarcoding in parallel with phospholipid fatty acid (PLFA) analysis. Quantitative estimates of the biomass of different taxonomic groups in samples were made through the analysis of PLFAs, and these were compared to the relative abundances of microbial taxa estimated from metabarcoding. Furthermore, we used the PLFA-based quantitative estimates of the biomass to adjust relative abundances of microbial groups determined by metabarcoding to provide insight into how the biomass of microbial taxa from PLFA analysis can improve understanding of microbial communities from environmental DNA samples. We used two sets of PLFA biomarkers that differed in their number of PLFAs to evaluate how PLFA biomarker selection influences biomass estimates. Metabarcoding and PLFA analysis provided significantly different views of bacterial composition, and these differences varied among substrates. We observed the most notable differences for the Gram-negative bacteria, which were overrepresented by metabarcoding in comparison to PLFA analysis. In contrast, the relative biomass and relative sequence abundances aligned reasonably well for Cyanobacteria across the tested freshwater substrates. Adjusting relative abundances of microbial taxa estimated by metabarcoding with PLFA-based quantification estimates of the microbial biomass led to significant changes in the microbial community compositions in all substrates. We recommend including independent estimates of the biomass of microbial groups to increase comparability among metabarcoding libraries from environmental samples, especially when comparing communities associated with different substrates.

Diagnostic performance of Ion 16S metagenomics kit and Ion reporter metagenomics workflow for bacterial pathogen detection in culture-negative clinical specimens from sterile sources

PCR-based deep sequencing of 16S rRNA gene allows for detection of a wide array of bacterial pathogens in culture-negative specimens. Ion 16S metagenomics kit and Ion Reporter metagenomics workflow (Ion 16S mNGS) provides an end-to-end solution with integrated workflow. Ninety-eight clinical samples with the diagnosis generated with 16S rRNA gene PCR/chain termination (Sanger) sequencing (16S CS) was used to assess the performance of Ion 16S mNGS. Compared to species level detection of 16S CS, the Ion 16S mNGS had 88% sensitivity and 76% specificity. When accounting for genus level of detection, the Ion 16S mNGS had 100% sensitivity. Notably, Ion 16S mNGS generated diagnosis in 13% of 16S CS and culture-negative samples. In addition, Ion 16S mNGS had the advantage of detecting more than 1 pathogen in 16S CS positive samples. We showed that the workflow had high reproducibility.

Managing Contamination and Diverse Bacterial Loads in 16S rRNA Deep Sequencing of Clinical Samples: Implications of the Law of Small Numbers

In this article, we investigate patterns of microbial DNA contamination in targeted 16S rRNA amplicon sequencing (16S deep sequencing) and demonstrate how this can be used to filter background bacterial DNA in diagnostic microbiology. We also investigate the importance of sequencing depth. We first determined the patterns of contamination by performing repeat 16S deep sequencing of negative and positive extraction controls. This process identified a few bacterial species dominating across all replicates but also a high intersample variability among low abundance contaminant species in replicates split before PCR amplification. Replicates split after PCR amplification yielded almost identical sequencing results. On the basis of these observations, we suggest using the abundance of the most dominant contaminant species to define a threshold in each clinical sample from where identifications with lower abundances possibly represent contamination. We evaluated this approach by sequencing of a diluted, staggered mock community and of bile samples from 41 patients with acute cholangitis and noninfectious bile duct stenosis. All clinical samples were sequenced twice using different sequencing depths. We were able to demonstrate the following: (i) The high intersample variability between sequencing replicates is caused by events occurring before or during the PCR amplification step. (ii) Knowledge about the most dominant contaminant species can be used to establish sample-specific cutoffs for reliable identifications. (iii) Below the level of the most abundant contaminant, it rapidly becomes very demanding to reliably discriminate between background and true findings. (iv) Adequate sequencing depth can be claimed only when the analysis also picks up background contamination.

Isolation and Characterization of Beneficial Bacteria from Food Process Wastes

Significant quantities of food waste are accumulated globally on an annual basis, with approximately one-third of the food produced (equivalent to 1.3 billion tons of food) being wasted each year. A potential food waste recycling application is its utilization as a soil conditioner or fertilizer, whereby it increases the soil organic content and microbial biomass. This study evaluated the effectiveness of food waste as a microbial resource by analyzing the microbial community composition and isolating plant growth-promoting bacteria (PGPB) in food waste obtained from various sources. High-throughput sequencing identified 393 bacterial operational taxonomic units in the food process waste (FPW) samples. Moreover, the results showed that Firmicutes was abundant in the waste samples, followed by Bacteroidetes and Proteobacteria. A total of 92 bacteria were isolated from FPW. Moreover, the cultivable strains isolated from FPW belonged to the genus Bacillus, followed by Streptomyces and Proteus. Six isolated bacteria exhibited beneficial traits, including indole acetic acid production, antifungal resistance and extracellular lysis. FPW is a valuable microbial resource for isolation of PGPB, and its use as a fertilizer may enable a reduction in chemical fertilizer usage, thereby mitigating the corresponding adverse environmental impacts on sustainable crop development.

Microbiota identified from preserved Anopheles

Background

Mosquito species from the Anopheles gambiae complex and the Anopheles funestus group are dominant African malaria vectors. Mosquito microbiota play vital roles in physiology and vector competence. Recent research has focused on investigating the mosquito microbiota, especially in wild populations. Wild mosquitoes are preserved and transported to a laboratory for analyses. Thus far, microbial characterization post-preservation has been investigated in only Aedes vexans and Culex pipiens. Investigating the efficacy of cost-effective preservatives has also been limited to AllProtect reagent, ethanol and nucleic acid preservation buffer. This study characterized the microbiota of African Anopheles vectors: Anopheles arabiensis (member of the An. gambiae complex) and An. funestus (member of the An. funestus group), preserved on silica desiccant and RNAlater^® solution.

Methods

Microbial composition and diversity were characterized using culture-dependent (midgut dissections, culturomics, MALDI-TOF MS) and culture-independent techniques (abdominal dissections, DNA extraction, next-generation sequencing) from laboratory (colonized) and field-collected mosquitoes. Colonized mosquitoes were either fresh (non-preserved) or preserved for 4 and 12 weeks on silica or in RNAlater^®. Microbiota were also characterized from field-collected An. arabiensis preserved on silica for 8, 12 and 16 weeks.

Results

Elizabethkingia anophelis and Serratia oryzae were common between both vector species, while Enterobacter cloacae and Staphylococcus epidermidis were specific to females and males, respectively. Microbial diversity was not influenced by sex, condition (fresh or preserved), preservative, or preservation time-period; however, the type of bacterial identification technique affected all microbial diversity indices.

Conclusions

This study broadly characterized the microbiota of An. arabiensis and An. funestus. Silica- and RNAlater^®-preservation were appropriate when paired with culture-dependent and culture-independent techniques, respectively. These results broaden the selection of cost-effective methods available for handling vector samples for downstream microbial analyses.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12936-021-03754-7.

Mapping the transcriptomic changes of endothelial compartment in human hippocampus across aging and mild cognitive impairment

Compromise of the vascular system has important consequences on cognitive abilities and neurodegeneration. The identification of the main molecular signatures present in the blood vessels of human hippocampus could provide the basis to understand and tackle these pathologies. As direct vascular experimentation in hippocampus is problematic, we achieved this information by computationally disaggregating publicly available whole microarrays data of human hippocampal homogenates. Three conditions were analyzed: 'Young Adults', 'Aged', and 'aged with Mild Cognitive Impairment' (MCI). The genes identified were contrasted against two independent data-sets. Here we show that the endothelial cells from the Younger Group appeared in an 'activated stage'. In turn, in the Aged Group, the endothelial cells showed a significant loss of response to shear stress, changes in cell adhesion molecules, increased inflammation, brain-insulin resistance, lipidic alterations, and changes in the extracellular matrix. Some specific changes in the MCI group were also detected. Noticeably, in this study the features arisen from the Aged Group (high tortuosity, increased bifurcations, and smooth muscle proliferation), pose the need for further experimental verification to discern between the occurrence of arteriogenesis and/or vascular remodeling by capillary arterialization. This article has an associated First Person interview with the first author of the paper.

Launching of the Anaemia Research Peruvian Cohort (ARPEC): a multicentre birth cohort project to explore the iron adaptive homeostasis, infant growth and development in three Peruvian regions

BACKGROUND

Preventing infantile anaemia and ensuring optimal growth and development during early childhood, particularly in resource-constrained settings, represent an ongoing public health challenge. Current responses are aligned to treatment-based solutions, instead of determining the roles of its inter-related causes. This project aims to assess and understand the complex interplay of eco-bio-social-political factors that determine infantile anaemia to inform policy, research design and prevention practices.

METHODS

This is a longitudinal birth cohort study including four components: (1) biological, will assess known blood markers of iron homeostasis and anaemia and stool microbiota to identify and genetically analyse the participants' flora; (2) ecological, will assess and map pollutants in air, water and soil and evaluate features of nutrition and perceived food security; (3) social, which will use different qualitative research methodologies to explore key stakeholders and informants' perceptions related to nutritional, environmental and anaemia topics, participant observations and a participatory approach and (4) a political analysis, to identify and assess the impact of policies, guidelines and programmes at all levels for infantile anaemia in the three regions. Finally, we will also explore the role of social determinants and demographic variables longitudinally for all study participants. This project aims to contribute to the evidence of the inter-related causal factors of infantile anaemia, addressing the complexity of influencing factors from diverse methodological angles. We will assess infantile anaemia in three regions of Peru, including newborns and their mothers as participants, from childbirth until their first year of age.

ETHICS AND DISSEMINATION

Ethical approval was obtained from the Institutional Research Ethics Committee of the Instituto Nacional de Salud del Niño (Lima, Peru), CIEI-043-2019. An additional opinion has been granted by the Ethical Committee of Queen Mary University of London (London, UK). Dissemination across stakeholders is taking part as a continues part of the research process.

Faecal microbiome analysis reveals Clostridiales and Bacteroidales as signature gut microbes during estrus of buffalo

The non-pathogenic intestinal microbes that conquer our intestines are not an accidental jumble of organisms, but rather a disparate community of microbes that coexist, and sustain a mutualistic and symbiotic relationship with the host. The gut microbiome has been shown to be influenced by animal physiology and vice versa. However, information is still scanty. The present study aimed to analyse the variation between faecal bacteria of three different stages (proestrus, estrus and postestrus) of the estrous cycle of Murrah buffalos. A phylogenetic study of buffalo faeces derived from three different stages of estrous cycle was conducted in order to compare the bacterial diversity among these three stages. We performed an exploratory microbiome analysis of buffalo faeces using 16S rRNA sequencing during these stages of the buffalo estrous cycle. A total of three bacterial phyla with six different bacterial orders and twenty-three different genera were identified among all the three comparative phases of the estrous cycle. Among them, the Clostridiales were found to be the most abundant, and Bacteroidales were present exclusive during the estrus phase. As faeces is a source of gut microbes and a non-invasive representative of the metabolic steroids and perceptible pheromones, the profiling of gut microbes during estrous cycle would provide clues towards the major microbes contributing to the perceptible pheromones during estrus stage. To the best of our knowledge, this is the first ever report describing the faecal bacterial diversity during estrous cycle of any ruminant species. Although future studies are required to understand the role of Clostridiales and Bacteroidales in faecal pheromone metabolism.

DNA spike-ins enable confident interpretation of SARS-CoV-2 genomic data from amplicon-based sequencing

The rapid global spread and continued evolution of SARS-CoV-2 has highlighted an unprecedented need for viral genomic surveillance and clinical viral sequencing. Amplicon-based sequencing methods provide a sensitive, low-cost and rapid approach but suffer a high potential for contamination, which can undermine lab processes and results. This challenge will only increase with expanding global production of sequences by diverse research groups for epidemiological and clinical interpretation. We present an approach which uses synthetic DNA spike-ins (SDSIs) to track samples and detect inter-sample contamination through a sequencing workflow. Applying this approach to the ARTIC Consortium's amplicon design, we define a series of best practices for Illumina-based sequencing and provide a detailed characterization of approaches to increase sensitivity for low-viral load samples incorporating the SDSIs. We demonstrate the utility and efficiency of the SDSI method amidst a real-time investigation of a suspected hospital cluster of SARS-CoV-2 cases.

Indwelling Device-Associated Biofilms in Critically Ill Cancer Patients-Study Protocol

Health care-associated infections are a leading cause of inpatient complications. Rapid pathogen detection/identification is a major challenge in sepsis management that highly influences the successful outcome. The current standard of microorganism identification relies on bacterial growth in culture, which has several limitations. Gene sequencing research has developed culture-independent techniques for microorganism identification, with the aim to improve etiological diagnosis and, therefore, to change sepsis outcome. A prospective, observational, non-interventional, single-center study was designed that assesses biofilm-associated pathogens in a specific subpopulation of septic critically ill cancer patients. Indwelling device samples will be collected in septic patients at the moment of the removal of the arterial catheter, central venous catheter, endotracheal tube and urinary catheter. Concomitantly, clinical data regarding 4 sites (nasal, pharyngeal, rectal and skin) of pathogen colonization at the time of hospital/intensive care admission will be collected. The present study aims to offer new insights into biofilm-associated infections and to evaluate the infection caused by catheter-specific and patient-specific biofilm-associated pathogens in association with the extent of colonization. The analysis relies on the two following detection/identification techniques: standard microbiological method and next generation sequencing (NGS). Retrospectively, the study will estimate the clinical value of the NGS-based detection and its virtual potential in changing patient management and outcome, notably in the subjects with missing sepsis source or lack of response to anti-infective treatment.

Assessing the Use of Molecular Barcoding and qPCR for Investigating the Ecology of Prorocentrum minimum (Dinophyceae), a Harmful Algal Species

Prorocentrum minimum is a species of marine dinoflagellate that occurs worldwide and can be responsible for harmful algal blooms (HABs). Some studies have reported it to produce tetrodotoxin; however, results have been inconsistent. qPCR and molecular barcoding (amplicon sequencing) using high-throughput sequencing have been increasingly applied to quantify HAB species for ecological analyses and monitoring. Here, we isolated a strain of P. minimum from eastern Australian waters, where it commonly occurs, and developed and validated a qPCR assay for this species based on a region of ITS rRNA in relation to abundance estimates from the cultured strain as determined using light microscopy. We used this tool to quantify and examine ecological drivers of P. minimum in Botany Bay, an estuary in southeast Australia, for over ~14 months in 2016–2017. We compared abundance estimates using qPCR with those obtained using molecular barcoding based on an 18S rRNA amplicon. There was a significant correlation between the abundance estimates from amplicon sequencing and qPCR, but the estimates from light microscopy were not significantly correlated, likely due to the counting method applied. Using amplicon sequencing, ~600 unique actual sequence variants (ASVs) were found, much larger than the known phytoplankton diversity from this region. P. minimum abundance in Botany Bay was found to be significantly associated with lower salinities and higher dissolved CO₂ levels.

Relationship between dental and periodontal health status and the salivary microbiome: bacterial diversity, co-occurrence networks and predictive models

The present study used 16S rRNA gene amplicon sequencing to assess the impact on salivary microbiome of different grades of dental and periodontal disease and the combination of both (hereinafter referred to as oral disease), in terms of bacterial diversity, co-occurrence network patterns and predictive models. Our scale of overall oral health was used to produce a convenience sample of 81 patients from 270 who were initially recruited. Saliva samples were collected from each participant. Sequencing was performed in Illumina MiSeq with 2 × 300 bp reads, while the raw reads were processed according to the Mothur pipeline. The statistical analysis of the 16S rDNA sequencing data at the species level was conducted using the phyloseq, DESeq2, Microbiome, SpiecEasi, igraph, MixOmics packages. The simultaneous presence of dental and periodontal pathology has a potentiating effect on the richness and diversity of the salivary microbiota. The structure of the bacterial community in oral health differs from that present in dental, periodontal or oral disease, especially in high grades. Supragingival dental parameters influence the microbiota’s abundance more than subgingival periodontal parameters, with the former making a greater contribution to the impact that oral health has on the salivary microbiome. The possible keystone OTUs are different in the oral health and disease, and even these vary between dental and periodontal disease: half of them belongs to the core microbiome and are independent of the abundance parameters. The salivary microbiome, involving a considerable number of OTUs, shows an excellent discriminatory potential for distinguishing different grades of dental, periodontal or oral disease; considering the number of predictive OTUs, the best model is that which predicts the combined dental and periodontal status.

Emerging Options for the Diagnosis of Bacterial Infections and the Characterization of Antimicrobial Resistance

Precise and rapid identification and characterization of pathogens and antimicrobial resistance patterns are critical for the adequate treatment of infections, which represent an increasing problem in intensive care medicine. The current situation remains far from satisfactory in terms of turnaround times and overall efficacy. Application of an ineffective antimicrobial agent or the unnecessary use of broad-spectrum antibiotics worsens the patient prognosis and further accelerates the generation of resistant mutants. Here, we provide an overview that includes an evaluation and comparison of existing tools used to diagnose bacterial infections, together with a consideration of the underlying molecular principles and technologies. Special emphasis is placed on emerging developments that may lead to significant improvements in point of care detection and diagnosis of multi-resistant pathogens, and new directions that may be used to guide antibiotic therapy.

A Network Perspective on the Vectoring of Human Disease

Blood-sucking insects are important vectors of disease, with biting Diptera (flies) alone transmitting diseases that cause an estimated 700 000 human deaths a year. Insect vectors also bite nonhuman hosts, linking them into host-biting networks. While the major vectors of prominent diseases, such as malaria, yellow fever, dengue, and Zika, are intensively studied, there has been limited focus on the wider interactions of biting insects with nonhuman hosts. Drawing on network analysis and visualisation approaches from food-web ecology, we discuss the value of a network perspective for understanding host-insect-disease interactions, with a focus on Diptera vectors. Potential applications include highlighting pathways of disease transmission, highlighting reservoirs of infection, and identifying emerging and previously unrecognised vectors.

Vaginal microbial profiling in a preterm birth high-risk cohort using shallow shotgun metagenomics

Preterm birth (PTB) is a significant health problem globally, with an estimate of 15 million cases annually. Approximately 10% of neonates born early will die prematurely, while a subset will develop severe life-long morbidities. Unfortunately, preterm birth’s syndromic nature has evaded prevention strategies, and it continues to impose a high burden on healthcare systems and families. The role of vaginal bacteria in triggering biomolecular causes of PTB has been recognised for years. However, translating this knowledge to practical diagnostic and therapeutic strategies has remained elusive. New techniques in high-throughput sequencing have improved our understanding of the nature and role of the vaginal microbiome during pregnancy. Several multi-ethnic and multi-geographical studies into the vaginal microbiome have identified five distinct bacterial profiles termed community state types (CSTs), one of which is positively associated with dysbiosis and increased risk of PTB. In a small pilot study of first-trimester vaginal microbial DNA obtained from pregnant women at high-risk of PTB, we compared the CST profiles generated using standard 16S amplicon sequencing with shallow shotgun metagenomics (SSM). Both methods identified the presence of the five CSTs as has been reported previously, although the metagenomic data showed greater taxonomic resolution and more accurate CST assignation. These findings suggest that SSM is a cost-effective and potentially superior alternative to 16S sequencing for vaginal microbiome analysis.

Description of the bacterial microbiota of anal sacs in healthy dogs

The aim of the present study was to characterize the bacterial microbiota of anal sacs in healthy dogs using NGS. Swabs were used to sample the rectum and secretions from each anal sac in 15 healthy dogs. DNA was extracted from swabs and the V4 hypervariable region of the 16S rRNA gene was amplified and sequenced with Illumina MiSeq. Overall, 14 different bacterial phyla were identified in the rectum and in both anal sacs, the 5 main ones being Firmicutes, Bacteroidetes, Proteobacteria, Actinobacteria, and Fusobacteria. The rectum had higher microbial diversity and richness than the left and right anal sacs. Community membership and structure significantly differed between the rectum and both anal sacs, but not between the right and the left anal sacs. This study showed that the diversity and richness of the bacterial microbiota of the anal sacs in dogs is greater than what has been reported in previous studies with culture-based methods. In conclusion, the bacterial microbiota of the anal sacs in dogs varies between individuals and differs from the rectal bacterial microbiota.

Revisiting Plant-Microbe Interactions and Microbial Consortia Application for Enhancing Sustainable Agriculture: A Review

The present scenario of agricultural sector is dependent hugely on the use of chemical-based fertilizers and pesticides that impact the nutritional quality, health status, and productivity of the crops. Moreover, continuous release of these chemical inputs causes toxic compounds such as metals to accumulate in the soil and move to the plants with prolonged exposure, which ultimately impact the human health. Hence, it becomes necessary to bring out the alternatives to chemical pesticides/fertilizers for improvement of agricultural outputs. The rhizosphere of plant is an important niche with abundant microorganisms residing in it. They possess the properties of plant growth promotion, disease suppression, removal of toxic compounds, and assimilating nutrients to plants. Utilizing such beneficial microbes for crop productivity presents an efficient way to modulate the crop yield and productivity by maintaining healthy status and quality of the plants through bioformulations. To understand these microbial formulation compositions, it becomes essential to understand the processes going on in the rhizosphere as well as their concrete identification for better utilization of the microbial diversity such as plant growth–promoting bacteria and arbuscular mycorrhizal fungi. Hence, with this background, the present review article highlights the plant microbiome aboveground and belowground, importance of microbial inoculants in various plant species, and their subsequent interactive mechanisms for sustainable agriculture.

Cyanobacterial blooms in wastewater treatment facilities: Significance and emerging monitoring strategies

Municipal wastewater treatment facilities (WWTFs) are prone to the proliferation of cyanobacterial species which thrive in stable, nutrient-rich environments. Dense cyanobacterial blooms frequently disrupt treatment processes and the supply of recycled water due to their production of extracellular polymeric substances, which hinder microfiltration, and toxins, which pose a health risk to end-users. A variety of methods are employed by water utilities for the identification and monitoring of cyanobacteria and their toxins in WWTFs, including microscopy, flow cytometry, ELISA, chemoanalytical methods, and more recently, molecular methods. Here we review the literature on the occurrence and significance of cyanobacterial blooms in WWTFs and discuss the pros and cons of the various strategies for monitoring these potentially hazardous events. Particular focus is directed towards next-generation metagenomic sequencing technologies for the development of site-specific cyanobacterial bloom management strategies. Long-term multi-omic observations will enable the identification of indicator species and the development of site-specific bloom dynamics models for the mitigation and management of cyanobacterial blooms in WWTFs. While emerging metagenomic tools could potentially provide deep insight into the diversity and flux of problematic cyanobacterial species in these systems, they should be considered a complement to, rather than a replacement of, quantitative chemoanalytical approaches.