Metagenomics for pathogen detection in public health

FDA's proposed rule and its regulatory impact on emerging and reemerging neglected tropical diseases in the United States

Diagnosing infectious diseases significantly influences patient care, aiding in outbreak identification, response, and public health monitoring. However, the range of FDA-approved molecular tests remains notably limited, especially concerning neglected tropical diseases (NTDs). Drawing upon our experience as one of the largest healthcare networks in the greater New York metropolitan area, this viewpoint manuscript aims to spotlight the existing diagnostic landscape and unmet clinical needs for 4 emerging NTDs increasingly prevalent in the United States, additionally, it delves into the possible adverse effects of the FDA's Proposed Rule on Laboratory-Developed Tests for these clinical conditions and the broader spectrum of NTDs.

Strain-level characterization of foodborne pathogens without culture enrichment for outbreak investigation using shotgun metagenomics facilitated with nanopore adaptive sampling

Introduction

Shotgun metagenomics has previously proven effective in the investigation of foodborne outbreaks by providing rapid and comprehensive insights into the microbial contaminant. However, culture enrichment of the sample has remained a prerequisite, despite the potential impact on pathogen detection resulting from the growth competition. To circumvent the need for culture enrichment, we explored the use of adaptive sampling using various databases for a targeted nanopore sequencing, compared to shotgun metagenomics alone.

Methods

The adaptive sampling method was first tested on DNA of mashed potatoes mixed with DNA of a Staphylococcus aureus strain previously associated with a foodborne outbreak. The selective sequencing was used to either deplete the potato sequencing reads or enrich for the pathogen sequencing reads, and compared to a shotgun sequencing. Then, living S. aureus were spiked at 105 CFU into 25 g of mashed potatoes. Three DNA extraction kits were tested, in combination with enrichment using adaptive sampling, following whole genome amplification. After data analysis, the possibility to characterize the contaminant with the different sequencing and extraction methods, without culture enrichment, was assessed.

Results

Overall, the adaptive sampling outperformed the shotgun sequencing. While the use of a host removal DNA extraction kit and targeted sequencing using a database of foodborne pathogens allowed rapid detection of the pathogen, the most complete characterization was achieved when using solely a database of S. aureus combined with a conventional DNA extraction kit, enabling accurate placement of the strain on a phylogenetic tree alongside outbreak cases.

Discussion

This method shows great potential for strain-level analysis of foodborne outbreaks without the need for culture enrichment, thereby enabling faster investigations and facilitating precise pathogen characterization. The integration of adaptive sampling with metagenomics presents a valuable strategy for more efficient and targeted analysis of microbial communities in foodborne outbreaks, contributing to improved food safety and public health.

Pathogen profile of Baiyangdian Lake sediments using metagenomic analysis and their correlation with environmental factors

Increasing concerns about public health and safety after covid-19 have raised pathogen studies, especially in aquatic environments. However, the extent to how different location and human activities affect geographic occurrence and distribution of pathogens in response to agricultural pollution, boat tourism disturbances and municipal wastewater inflow in a degraded lake remains unclear. Since the surrounding residents depend on the lake for their livelihood, understanding the pathogens reserved in lake sediment and the regulation possibility by environmental factors are challenges with far-reaching significance. Results showed that 187 pathogens were concurrently shared by the nine sediment samples, with Salmonella enterica and Pseudomonas aeruginosa being the most abundant. The similar composition of the pathogens suggests that lake sediment may act as reservoirs of generalist pathogens which may pose infection risk to a wide range of host species. Of the four virulence factors (VFs) types analyzed, offensive VFs were dominant (>46 % on average) in all samples, with dominant subtypes including adherence, secretion systems and toxins. Notably, the lake sediments under the impact of agricultural use (g1) showed significantly higher diversity and abundance of pathogen species and VFs than those under the impact of boat tourism (g2) and/or municipal wastewater inflow with reed marshes filtration (g3). From the co-occurrence networks, pathogens and pesticides, aggregate fractions, EC, pH, phosphatase have strong correlations. Strong positive correlations between pathogens and diazinon in g1 and ppDDT in g2 and g3 suggest higher pesticide-pathogen co-exposure risk. These findings highlight the need to explore pathogen - environmental factor interaction mechanisms in the human-impacted water environments where the control of pathogen invasion by environmental factors may accessible.

Profiling pathogenic protozoan and their functional pathways in wastewater using 18S rRNA and shotgun metagenomics

Despite extensive research, little is known about the composition of eukaryotic protists in environmental samples. This is due to low parasite concentrations, the complexity of parasite diversity, and a lack of suitable reference databases and standardized protocols. To bridge this knowledge gap, this study used 18S rRNA short amplicon and shotgun metagenomic sequencing approaches to profile protozoan microbial communities as well as their functional pathways in treated and untreated wastewater samples collected from different regions of South Africa. Results demonstrated that protozoan diversity (Shannon index P-value = 0.03) and taxonomic composition (PERMANOVA, P-value = 0.02) was mainly driven by the type of wastewater samples (treated & untreated) and geographic location. However, these WWTPs were also found to contain a core community of protozoan parasites. The untreated wastewater samples revealed a predominant presence of free-living, parasitic, and potentially pathogenic protists typically found in humans and animals, ranging from Alveolata (27 %) phylum (Apicomplexa and Ciliophora) to Excavata (3.88 %) (Discoba and Parasalia) and Amoebozoa (2.84 %) (Entamoeba and Acanthamoeba). Shotgun metagenomics analyses in a subset of the untreated wastewater samples confirmed the presence of public health-importance protozoa, including Cryptosporidium species (3.48 %), Entamoeba hystolitica (6.58 %), Blastocystis hominis (2.91 %), Naegleria gruberi (2.37 %), Toxoplasma gondii (1.98 %), Cyclospora cayetanensis (1.30 %), and Giardia intestinalis (0.31 %). Virulent gene families linked to pathogenic protozoa, such as serine/threonine protein phosphatase and mucin-desulfating sulfatase were identified. Additionally, enriched pathways included thiamine diphosphate biosynthesis III, heme biosynthesis, Methylerythritol 4-Phosphate Pathway, methyl erythritol phosphate (MEP), and pentose phosphate pathways. These findings suggest that protozoan pathogens may possess metabolic and growth potential within WWTPs, posing a severe risk of transmission to humans and animals if inadequately disinfected before release. This study provides a baseline for the future investigation of diverse protozoal communities in wastewater, which are of public health importance.

Identification of potential microbial risk factors associated with fecal indicator exceedances at recreational beaches

BACKGROUND

Fecal bacterial densities are proxy indicators of beach water quality, and beach posting decisions are made based on Beach Action Value (BAV) exceedances for a beach. However, these traditional beach monitoring methods do not reflect the full extent of microbial water quality changes associated with BAV exceedances at recreational beaches (including harmful cyanobacteria). This proof of concept study evaluates the potential of metagenomics for comprehensively assessing bacterial community changes associated with BAV exceedances compared to non-exceedances for two urban beaches and their adjacent river water sources.

RESULTS

Compared to non-exceedance samples, BAV exceedance samples exhibited higher alpha diversity (diversity within the sample) that could be further differentiated into separate clusters (Beta-diversity). For Beach A, Cyanobacterial sequences (resolved as Microcystis and Pseudanabaena at genus level) were significantly more abundant in BAV non-exceedance samples. qPCR validation supported the Cyanobacterial abundance results from metagenomic analysis and also identified saxitoxin genes in 50% of the non-exceedance samples. Microcystis sp and saxitoxin gene sequences were more abundant on non-exceedance beach days (when fecal indicator data indicated the beach should be open for water recreational purposes). For BAV exceedance days, Fibrobacteres, Pseudomonas, Acinetobacter, and Clostridium sequences were significantly more abundant (and positively correlated with fecal indicator densities) for Beach A. For Beach B, Spirochaetes (resolved as Leptospira on genus level) Burkholderia and Vibrio sequences were significantly more abundant in BAV exceedance samples. Similar bacterial diversity and abundance trends were observed for river water sources compared to their associated beaches. Antibiotic Resistance Genes (ARGs) were also consistently detected at both beaches. However, we did not observe a significant difference or correlation in ARGs abundance between BAV exceedance and non-exceedance samples.

CONCLUSION

This study provides a more comprehensive analysis of bacterial community changes associated with BAV exceedances for recreational freshwater beaches. While there were increases in bacterial diversity and some taxa of potential human health concern associated with increased fecal indicator densities and BAV exceedances (e.g. Pseudomonas), metagenomics analyses also identified other taxa of potential human health concern (e.g. Microcystis) associated with lower fecal indicator densities and BAV non-exceedances days. This study can help develop more targeted beach monitoring strategies and beach-specific risk management approaches.

Multi-aptamer-mediated hairpin allosteric and aptamer-assisted CRISPR system for detection of S. pneumoniae and S. aureus

A novel nucleic acid aptamer nanoprobes-mediated hairpin allosteric and aptamer-assisted CRISPR system for detection of Streptococcus pneumoniae and Staphylococcus aureus is presented. In this fluorescence assay system, utilizing the hairpin allosteric effect caused by the aptamer binding to the target bacteria, the detection of S. pneumoniae is first achieved through changes in fluorescence due to FRET. Subsequently, a Cas12a protein mixture is added to detect S. aureus. The amplified output signal is triggered by two methods to ensure the sensitivity of the method: the synergistic FRET effect is achieved by the assembly of multi-aptamer through the conjugation of streptavidin-biotin, and the trans-cleavage function of CRISPR/Cas 12a. Under the optimized conditions, the proposed hairpin allosteric aptasensor could achieve high sensitivity (a detection limit of 135 cfu/mL) and broad-concentration quantification (dynamic range of 103-107 cfu/mL) of S. pneumoniae. The aptamer-assisted CRISPR system for S. aureus detection showed good linearity (R2 = 0.996) in the concentration range 102-108 cfu/mL, with a detection limit of 39 cfu/mL. No cross-reactivity with other foodborne pathogenic bacteria was observed in both systems. Taking only 55 min, this method of multiple pathogen detection proved to be promising.

Addressing the Knowledge Deficit in Hospital Bed Planning and Defining an Optimum Region for the Number of Different Types of Hospital Beds in an Effective Health Care System

Based upon 30-years of research by the author, a new approach to hospital bed planning and international benchmarking is proposed. The number of hospital beds per 1000 people is commonly used to compare international bed numbers. This method is flawed because it does not consider population age structure or the effect of nearness-to-death on hospital utilization. Deaths are also serving as a proxy for wider bed demand arising from undetected outbreaks of 3000 species of human pathogens. To remedy this problem, a new approach to bed modeling has been developed that plots beds per 1000 deaths against deaths per 1000 population. Lines of equivalence can be drawn on the plot to delineate countries with a higher or lower bed supply. This method is extended to attempt to define the optimum region for bed supply in an effective health care system. England is used as an example of a health system descending into operational chaos due to too few beds and manpower. The former Soviet bloc countries represent a health system overly dependent on hospital beds. Several countries also show evidence of overutilization of hospital beds. The new method is used to define a potential range for bed supply and manpower where the most effective health systems currently reside. The method is applied to total curative beds, medical beds, psychiatric beds, critical care, geriatric care, etc., and can also be used to compare different types of healthcare staff, i.e., nurses, physicians, and surgeons. Issues surrounding the optimum hospital size and the optimum average occupancy will also be discussed. The role of poor policy in the English NHS is used to show how the NHS has been led into a bed crisis. The method is also extended beyond international benchmarking to illustrate how it can be applied at a local or regional level in the process of long-term bed planning. Issues regarding the volatility in hospital admissions are also addressed to explain the need for surge capacity and why an adequate average bed occupancy margin is required for an optimally functioning hospital.

Preparation for the next pandemic: challenges in strengthening surveillance

The devastating Coronavirus Disease 2019 (COVID-19) pandemic indicates that early detection of candidates with pandemic potential is vital. However, comprehensive metagenomic sequencing of the total microbiome is not practical due to the astronomical and rapidly evolving numbers and species of micro-organisms. Analysis of previous pandemics suggests that an increase in human-animal interactions, changes in animal and arthropod distribution due to climate change and deforestation, continuous mutations and interspecies jumping of RNA viruses, and frequent travels are important factors driving pandemic emergence. Besides measures mitigating these factors, surveillance at human-animal interfaces targeting animals with unusual tolerance to viral infections, sick heathcare workers, and workers at high biosafety level laboratories is crucial. Surveillance of sick travellers is important when alerted by an early warning system of a suspected outbreak due to unknown agents. These samples should be screened by multiplex nucleic acid amplification and subsequent unbiased next-generation sequencing. Novel viruses should be isolated in routine cell cultures, complemented by organoid cultures, and then tested in animal models for interspecies transmission potential. Potential agents are candidates for designing rapid diagnostics, therapeutics, and vaccines. For early detection of outbreaks, there are advantages in using event-based surveillance and artificial intelligence (AI), but high background noise and censorship are possible drawbacks. These systems are likely useful if they channel reliable information from frontline healthcare or veterinary workers and large international gatherings. Furthermore, sufficient regulation of high biosafety level laboratories, and stockpiling of broad spectrum antiviral drugs, vaccines, and personal protective equipment are indicated for pandemic preparedness.

Diagnosis of leptospira by metagenomics next-generation sequencing with extracorporeal membrane oxygenation support: a case report

BACKGROUND

Leptospirosis is an infectious disease caused by pathogenic Leptospira spp., which could result in severe illnesses. Indirect contact with these pathogens is more common. Individuals could contract this disease through contact with contaminated water or during floods. In this case, we present the details of a 40-year-old male pig farmer who suffered from severe pulmonary hemorrhagic leptospirosis and multiple organ failure. The diagnosis of leptospirosis was confirmed through metagenomics next-generation sequencing (mNGS) while the patient received extracorporeal membrane oxygenation (ECMO) support, and antibiotic treatment was adjusted accordingly. The patient underwent comprehensive treatment and rehabilitation in the intensive care unit.

CONCLUSION

This case illustrates the importance of early diagnosis and treatment of leptospirosis. While obtaining the epidemiological history, second-generation metagenomics sequencing was utilized to confirm the etiology. The prompt initiation of ECMO therapy provided a crucial window of opportunity for addressing the underlying cause. This case report offers valuable insights for diagnosing patients with similar symptoms.

Recent Advances in Metagenomic Approaches, Applications, and Challenge

Advances in metagenomics analysis with the advent of next-generation sequencing have extended our knowledge of microbial communities as compared to conventional techniques providing advanced approach to identify novel and uncultivable microorganisms based on their genetic information derived from a particular environment. Shotgun metagenomics involves investigating the DNA of the entire community without the requirement of PCR amplification. It provides access to study all genes present in the sample. On the other hand, amplicon sequencing targets taxonomically important marker genes, the analysis of which is restricted to previously known DNA sequences. While sequence-based metagenomics is used to analyze DNA sequences directly from the environment without the requirement of library construction and with limited identification of novel genes and products that can be complemented by functional genomics, function-based metagenomics requires fragmentation and cloning of extracted metagenome DNA in a suitable host with subsequent functional screening and sequencing clone for detection of a novel gene. Although advances were made in metagenomics, different challenges arise. This review provides insight into advances in the metagenomic approaches combined with next-generation sequencing, their recent applications highlighting the emerging ones, such as in astrobiology, forensic sciences, and SARS-CoV-2 infection diagnosis, and the challenges associated. This review further discusses the different types of metagenomics and outlines advancements in bioinformatics tools and their significance in the analysis of metagenomic datasets.

Pragmatic Considerations When Extracting DNA for Metagenomics Analyses of Clinical Samples

Microbiome analyses are essential for understanding microorganism composition and diversity, but interpretation is often challenging due to biological and technical variables. DNA extraction is a critical step that can significantly bias results, particularly in samples containing a high abundance of challenging-to-lyse microorganisms. Taking into consideration the distinctive microenvironments observed in different bodily locations, our study sought to assess the extent of bias introduced by suboptimal bead-beating during DNA extraction across diverse clinical sample types. The question was whether complex targeted extraction methods are always necessary for reliable taxonomic abundance estimation through amplicon sequencing or if simpler alternatives are effective for some sample types. Hence, for four different clinical sample types (stool, cervical swab, skin swab, and hospital surface swab samples), we compared the results achieved from extracting targeted manual protocols routinely used in our research lab for each sample type with automated protocols specifically not designed for that purpose. Unsurprisingly, we found that for the stool samples, manual extraction protocols with vigorous bead-beating were necessary in order to avoid erroneous taxa proportions on all investigated taxonomic levels and, in particular, false under- or overrepresentation of important genera such as Blautia, Faecalibacterium, and Parabacteroides. However, interestingly, we found that the skin and cervical swab samples had similar results with all tested protocols. Our results suggest that the level of practical automation largely depends on the expected microenvironment, with skin and cervical swabs being much easier to process than stool samples. Prudent consideration is necessary when extending the conclusions of this study to applications beyond rough estimations of taxonomic abundance.

A Novel Simian Adenovirus Associating with Human Adeno-virus Species G Isolated from Long-Tailed Macaque Feces

Metagenomics has demonstrated its capability in outbreak investigations and pathogen surveillance and discovery. With high-throughput and effective bioinformatics, many disease-causing agents, as well as novel viruses of humans and animals, have been identified using metagenomic analysis. In this study, a VIDISCA metagenomics workflow was used to identify potential unknown viruses in 33 fecal samples from asymptomatic long-tailed macaques (Macaca fascicularis) in Ratchaburi Province, Thailand. Putatively novel astroviruses, enteroviruses, and adenoviruses were detected and confirmed by PCR analysis of long-tailed macaque fecal samples collected from areas in four provinces, Ratchaburi, Kanchanaburi, Lopburi, and Prachuap Khiri Khan, where humans and monkeys live in proximity (total n = 187). Astroviruses, enteroviruses, and adenoviruses were present in 3.2%, 7.5%, and 4.8% of macaque fecal samples, respectively. One adenovirus, named AdV-RBR-6-3, was successfully isolated in human cell culture. Whole-genome analysis suggested that it is a new member of the species Human adenovirus G, closely related to Rhesus adenovirus 53, with evidence of genetic recombination and variation in the hexon, fiber, and CR1 genes. Sero-surveillance showed neutralizing antibodies against AdV-RBR-6-3 in 2.9% and 11.2% of monkeys and humans, respectively, suggesting cross-species infection of monkeys and humans. Overall, we reported the use of metagenomics to screen for possible new viruses, as well as the isolation and molecular and serological characterization of the new adenovirus with cross-species transmission potential. The findings emphasize that zoonotic surveillance is important and should be continued, especially in areas where humans and animals interact, to predict and prevent the threat of emerging zoonotic pathogens.

High-throughput sequencing approaches applied to SARS-CoV-2

High-throughput sequencing is crucial for surveillance and control of viral outbreaks. During the ongoing coronavirus disease 2019 (COVID-19) pandemic, advances in the high-throughput sequencing technology resources have enhanced diagnosis, surveillance, and vaccine discovery. From the onset of the pandemic in December 2019, several genome-sequencing approaches have been developed and supported across the major sequencing platforms such as Illumina, Oxford Nanopore, PacBio, MGI DNBSEQTM and Ion Torrent. Here, we share insights from the sequencing approaches developed for sequencing of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) between December 2019 and October 2022.

Agnostic Sequencing for Detection of Viral Pathogens

The advent of next-generation sequencing (NGS) technologies has expanded our ability to detect and analyze microbial genomes and has yielded novel molecular approaches for infectious disease diagnostics. While several targeted multiplex PCR and NGS-based assays have been widely used in public health settings in recent years, these targeted approaches are limited in that they still rely on a priori knowledge of a pathogen's genome, and an untargeted or unknown pathogen will not be detected. Recent public health crises have emphasized the need to prepare for a wide and rapid deployment of an agnostic diagnostic assay at the start of an outbreak to ensure an effective response to emerging viral pathogens. Metagenomic techniques can nonspecifically sequence all detectable nucleic acids in a sample and therefore do not rely on prior knowledge of a pathogen's genome. While this technology has been reviewed for bacterial diagnostics and adopted in research settings for the detection and characterization of viruses, viral metagenomics has yet to be widely deployed as a diagnostic tool in clinical laboratories. In this review, we highlight recent improvements to the performance of metagenomic viral sequencing, the current applications of metagenomic sequencing in clinical laboratories, as well as the challenges that impede the widespread adoption of this technology.

Genetic characterization of human adenoviruses in patients using metagenomic next-generation sequencing in Hubei, China, from 2018 to 2019

Objectives

This study aimed to characterize the genomic epidemiology of human adenoviruses (HAdVs) in Hubei, China, using metagenomic next-generation sequencing (mNGS).

Methods

In total, 25 HAdV-positive samples collected from 21 pediatric patients were sequenced and subjected to mNGS using the NextSeq 550 and GenoLab M sequencing platforms. The metagenomic data were assembled de novo for molecular typing, phylogenetic and recombination analyzes.

Results

We assembled 50 HAdV genomes, 88% (22/25) genomes from GenoLab M, and 84% (21/25) genomes from NextSeq 550 have perfect alignments to reference genomes with greater than 90%. The most fully assembled 25 genomes were categorized into 7 HAdV genotypes, the most abundant of which were HAdV-B3 (9/25) and HAdV-C2 (6/25). Phylogenetic analyzes revealed that the newly isolated HAdV-B3 strains diverged into separate clusters according to their genotypes. Vigilance is needed that HAdV-B3 isolates have begun to form new distinct clusters. High nucleotide identity was observed in the whole genome level within the same HAdV genotypes, while marked differences of three capsid genes across HAdV genotypes were noted. The high nucleotide diversity regions were concordant with the reported hypervariable regions. Further, three recombinant strains were identified: S64 and S71 originated from the parental strains HAdV-B14 and HAdV-B11, and S28 originated from HAdV-C1, HAdV-C5, and HAdV-CBJ113. GenoLab M and NextSeq 550 showed comparable performance with respect to data yield, duplication rate, human ratio, and assembly completeness.

Conclusion

The sequencing quality and assembly accuracy showed that mNGS assembled genomes can be used for subsequently HAdV genotyping and genomic characterization. The high nucleotide diversity of capsid genes and high frequency of recombination events has highlighted the necessity for HAdV epidemiological surveillance in China.

Valorization as a biofertilizer of an agricultural residue leachate: Metagenomic characterization and growth promotion test by PGPB in the forage plant Medicago sativa (alfalfa)

The abuse of chemical fertilizers in intensive agriculture has turned out in the contamination of ground and the soil on which they are applied. Likewise, the generation, storage, and destruction of plant residues from the agri-food industry poses a threat to the environment and human health. The current situation of growing demand for food implies the urgent need to find sustainable alternatives to chemical fertilizers and the management of agricultural waste. Valorization of this plant residue to produce natural biofertilizers using microbiological treatments is presented as a sustainable alternative. The microbial activity allows the transformation into simple molecules that are easily absorbed by plants, as well as the stimulation of plant growth. This double direct and indirect action induced significant increases against the variables of germination, viability, and biomass (dry weight). To guarantee biosafety, it is necessary to use new bio-technological tools, such as metagenomics, which allow the taxonomic analysis of microbial communities, detecting the absence of pathogens. In the present paper, a physicochemical and metagenomic characterization of a fertilizer obtained from agricultural plant waste valorization is carried out. Likewise, fertigation treatments were tested to which the Plant Growth Promoting Bacteria (PGPB) Pseudomonas agronomica and Bacillus pretiosus were added, both independently and in consortium. Metagenomic analysis has identified taxa belonging to the kingdoms Bacteria and Archaea; 10 phyla, 25 families, 32 genera and 34 species, none of them previously described as pathogenic. A 1/512 dilution of the fertilizer increased the germination rate of Medicago sativa (alfalfa) by 16% at 144 h, compared to the treatment without fertilizer. Both the fertilizer and the addition of PGPB in a double direct and indirect action induced significant increases against the variables of germination, viability, and biomass (dry weight). Therefore, the use of an agricultural residue is proposed, which after the addition of two new species is transformed into a biofertilizer that significantly induces plant growth in Mendicago sativa plants.

Microbial Inoculants as Plant Biostimulants: A Review on Risk Status

Modern agriculture systems are copiously dependent on agrochemicals such as chemical fertilizers and pesticides intended to increase crop production and yield. The indiscriminate use of these chemicals not only affects the growth of plants due to the accumulation of toxic compounds, but also degrades the quality and life-supporting properties of soil. There is a dire need to develop some green approach that can resolve these issues and restore soil fertility and sustainability. The use of plant biostimulants has emerged as an environmentally friendly and acceptable method to increase crop productivity. Biostimulants contain biological substances which may be capable of increasing or stimulating plant growth in an eco-friendly manner. They are mostly biofertilizers that provide nutrients and protect plants from environmental stresses such as drought and salinity. In contrast to the protection of crop products, biostimulants not only act on the plant's vigor but also do not respond to direct actions against pests or diseases. Plant biostimulants improve nutrient mobilization and uptake, tolerance to stress, and thus crop quality when applied to plants directly or in the rhizospheric region. They foster plant growth and development by positively affecting the crop life-cycle starting from seed germination to plant maturity. Legalized application of biostimulants causes no hazardous effects on the environment and primarily provides nutrition to plants. It nurtures the growth of soil microorganisms, which leads to enhanced soil fertility and also improves plant metabolism. Additionally, it may positively influence the exogenous microbes and alter the equilibrium of the microfloral composition of the soil milieu. This review frequently cites the characterization of microbial plant biostimulants that belong to either a high-risk group or are closely related to human pathogens such as Pueudomonas, Klebsiella, Enterobacter, Acinetobacter, etc. These related pathogens cause ailments including septicemia, gastroenteritis, wound infections, inflammation in the respiratory system, meningitis, etc., of varied severity under different conditions of health status such as immunocompromized and comorbidity. Thus it may attract the related concern to review the risk status of biostimulants for their legalized applications in agriculture. This study mainly emphasizes microbial plant biostimulants and their safe application concerns.

Metagenomics Next Generation Sequencing (mNGS): An Exciting Tool for Early and Accurate Diagnostic of Fungal Pathogens in Plants

Crop output is directly impacted by infections, with fungi as the major plant pathogens, making accurate diagnosis of these threats crucial. Developing technology and multidisciplinary approaches are turning to genomic analyses in addition to traditional culture methods in diagnostics of fungal plant pathogens. The metagenomic next-generation sequencing (mNGS) method is preferred for genotyping identification of organisms, identification at the species level, illumination of metabolic pathways, and determination of microbiota. Moreover, the data obtained so far show that this new approach is promising as an emerging new trend in fungal disease detection. Another approach covered by mNGS technologies, known as metabarcoding, enables use of specific markers specific to a genetic region and allows for genotypic identification by facilitating the sequencing of certain regions. Although the core concept of mNGS remains constant across applications, the specific sequencing methods and bioinformatics tools used to analyze the data differ. In this review, we focus on how mNGS technology, including metabarcoding, is applied for detecting fungal pathogens and its promising developments for the future.

MTSv: rapid alignment-based taxonomic classification and high-confidence metagenomic analysis

As the size of reference sequence databases and high-throughput sequencing datasets continue to grow, it is becoming computationally infeasible to use traditional alignment to large genome databases for taxonomic classification of metagenomic reads. Exact matching approaches can rapidly assign taxonomy and summarize the composition of microbial communities, but they sacrifice accuracy and can lead to false positives. Full alignment tools provide higher confidence assignments and can assign sequences from genomes that diverge from reference sequences; however, full alignment tools are computationally intensive. To address this, we designed MTSv specifically for alignment-based taxonomic assignment in metagenomic analysis. This tool implements an FM-index assisted q-gram filter and SIMD accelerated Smith-Waterman algorithm to find alignments. However, unlike traditional aligners, MTSv will not attempt to make additional alignments to a TaxID once an alignment of sufficient quality has been found. This improves efficiency when many reference sequences are available per taxon. MTSv was designed to be flexible and can be modified to run on either memory or processor constrained systems. Although MTSv cannot compete with the speeds of exact k-mer matching approaches, it is reasonably fast and has higher precision than popular exact matching approaches. Because MTSv performs a full alignment it can classify reads even when the genomes share low similarity with reference sequences and provides a tool for high confidence pathogen detection with low off-target assignments to near neighbor species.

Diagnostic Methods of Common Intestinal Protozoa: Current and Future Immunological and Molecular Methods

Intestinal protozoan infection is a persisting public health problem affecting the populations of developing countries in the tropical and subtropical regions. The diagnosis of intestinal protozoa remains a challenge especially in developing countries due to a shortage of laboratory facilities, limited health funding, and the remoteness of communities. Despite still being widely used, conventional diagnoses using microscopy and staining methods pose important limitations, particularly due to their low sensitivities and specificities. The selection of diagnostic methods needs to be carefully considered based on the objective of examination, availability of resources, and the expected parasite to be found. In this review, we describe various immunodiagnosis and molecular diagnostic methods for intestinal protozoa infection, including their advantages, disadvantages, and suitability for different settings, with a focus on Entamoeba histolytica, Giardia duodenalis, and Cryptosporidium spp.

Using Genomics to Understand the Epidemiology of Infectious Diseases in the Northern Territory of Australia

The Northern Territory (NT) is a geographically remote region of northern and central Australia. Approximately a third of the population are First Nations Australians, many of whom live in remote regions. Due to the physical environment and climate, and scale of social inequity, the rates of many infectious diseases are the highest nationally. Molecular typing and genomic sequencing in research and public health have provided considerable new knowledge on the epidemiology of infectious diseases in the NT. We review the applications of genomic sequencing technology for molecular typing, identification of transmission clusters, phylogenomics, antimicrobial resistance prediction, and pathogen detection. We provide examples where these methodologies have been applied to infectious diseases in the NT and discuss the next steps in public health implementation of this technology.

Improving the sensitivity of lateral flow immunoassay for Salmonella typhimurium detection via flow-rate regulation

Application of the traditional immunochromatographic assay (ICGA) has been limited by its poor sensitivity. The objective of this study was to increase the sensitivity of the traditional ICGA. A dual-mode ICGA (D-M ICGA) was developed by combining a nanozyme-assisted signal-amplification strategy with a magnetic-nanoparticle-based flow-speed-control strategy. Salmonella typhimurium can be detected simultaneously based on color and magnetic signals in the detection area of the D-M ICGA strip. The calculated limits of detection of 50 cfu·mL^-1 and 75 cfu·mL^-1 in the color and magnetic modes, respectively, were approximately 1000 times lower than those of the traditional ICGA. The selectivity and practical applicability of the D-M ICGA were also confirmed in this study. The results prove that the D-M ICGA is an assay that could be used for Salmonella typhimurium detection and can be easily adapted to detect other pathogenic bacteria.

Large Scale Genome-Centric Metagenomic Data from the Gut Microbiome of Food-Producing Animals and Humans

The One Health concept is a global strategy to study the relationship between human and animal health and the transfer of pathogenic and non-pathogenic species between these systems. However, to the best of our knowledge, no data based on One Health genome-centric metagenomics are available in public repositories. Here, we present a dataset based on a pilot-study of 2,915 metagenome-assembled genomes (MAGs) of 107 samples from the human (N = 34), cattle (N = 28), swine (N = 15) and poultry (N = 30) gut microbiomes. Samples were collected from the five Brazilian geographical regions. Of the draft genomes, 1,273 were high-quality drafts (≥90% of completeness and ≤5% of contamination), and 1,642 were medium-quality drafts (≥50% of completeness and ≤10% of contamination). Taxonomic predictions were based on the alignment and concatenation of single-marker genes, and the most representative phyla were Bacteroidota, Firmicutes, and Proteobacteria. Many of these species represent potential pathogens that have already been described or potential new families, genera, and species with potential biotechnological applications. Analyses of this dataset will highlight discoveries about the ecology and functional role of pathogens and uncultivated Archaea and Bacteria from food-producing animals and humans. Furthermore, it also represents an opportunity to describe new species from underrepresented taxonomic groups.

Measurement(s)	Metagenome
Technology Type(s)	Illumina Sequencing

Predicting the pathogenicity of bacterial genomes using widely spread protein families

Background

The human body is inhabited by a diverse community of commensal non-pathogenic bacteria, many of which are essential for our health. By contrast, pathogenic bacteria have the ability to invade their hosts and cause a disease. Characterizing the differences between pathogenic and commensal non-pathogenic bacteria is important for the detection of emerging pathogens and for the development of new treatments. Previous methods for classification of bacteria as pathogenic or non-pathogenic used either raw genomic reads or protein families as features. Using protein families instead of reads provided a better interpretability of the resulting model. However, the accuracy of protein-families-based classifiers can still be improved.

Results

We developed a wide scope pathogenicity classifier (WSPC), a new protein-content-based machine-learning classification model. We trained WSPC on a newly curated dataset of 641 bacterial genomes, where each genome belongs to a different species. A comparative analysis we conducted shows that WSPC outperforms existing models on two benchmark test sets. We observed that the most discriminative protein-family features in WSPC are widely spread among bacterial species. These features correspond to proteins that are involved in the ability of bacteria to survive and replicate during an infection, rather than proteins that are directly involved in damaging or invading the host.

Metaomics in Clinical Laboratory: Potential Driving Force for Innovative Disease Diagnosis

Currently, more and more studies suggested that reductionism was lack of holistic and integrative view of biological processes, leading to limited understanding of complex systems like microbiota and the associated diseases. In fact, microbes are rarely present in individuals but normally live in complex multispecies communities. With the recent development of a variety of metaomics techniques, microbes could be dissected dynamically in both temporal and spatial scales. Therefore, in-depth understanding of human microbiome from different aspects such as genomes, transcriptomes, proteomes, and metabolomes could provide novel insights into their functional roles, which also holds the potential in making them diagnostic biomarkers in many human diseases, though there is still a huge gap to fill for the purpose. In this mini-review, we went through the frontlines of the metaomics techniques and explored their potential applications in clinical diagnoses of human diseases, e.g., infectious diseases, through which we concluded that novel diagnostic methods based on human microbiomes shall be achieved in the near future, while the limitations of these techniques such as standard procedures and computational challenges for rapid and accurate analysis of metaomics data in clinical settings were also examined.

Rapid Detection of Bacterial Pathogens and Antimicrobial Resistance Genes in Clinical Urine Samples With Urinary Tract Infection by Metagenomic Nanopore Sequencing

Urinary tract infections (UTIs) are among the most common acquired bacterial infections in humans. The current gold standard method for identification of uropathogens in clinical laboratories is cultivation. However, culture-based assays have substantial drawbacks, including long turnaround time and limited culturability of many potential pathogens. Nanopore sequencing technology can overcome these limitations and detect pathogens while also providing reliable predictions of drug susceptibility in clinical samples. Here, we optimized a metagenomic nanopore sequencing (mNPS) test for pathogen detection and identification in urine samples of 76 patients with acute uncomplicated UTIs. We first used twenty of these samples to show that library preparation by the PCR Barcoding Kit (PBK) led to the highest agreement of positive results with gold standard clinical culture tests, and enabled antibiotic resistance detection in downstream analyses. We then compared the detection results of mNPS with those of culture-based diagnostics and found that mNPS sensitivity and specificity of detection were 86.7% [95% confidence interval (CI), 73.5-94.1%] and 96.8% (95% CI, 82.4-99.9%), respectively, indicating that the mNPS method is a valid approach for rapid and specific detection of UTI pathogens. The mNPS results also performed well at predicting antibiotic susceptibility phenotypes. These results demonstrate that our workflow can accurately diagnose UTI-causative pathogens and enable successful prediction of drug-resistant phenotypes within 6 h of sample receipt. Rapid mNPS testing is thus a promising clinical diagnostic tool for infectious diseases, based on clinical urine samples from UTI patients, and shows considerable potential for application in other clinical infections.

Identification of Antibiotic Resistance Proteins via MiCId's Augmented Workflow. A Mass Spectrometry-Based Proteomics Approach

Fast and accurate identifications of pathogenic bacteria along with their associated antibiotic resistance proteins are of paramount importance for patient treatments and public health. To meet this goal from the mass spectrometry aspect, we have augmented the previously published Microorganism Classification and Identification (MiCId) workflow for this capability. To evaluate the performance of this augmented workflow, we have used MS/MS datafiles from samples of 10 antibiotic resistance bacterial strains belonging to three different species: Escherichia coli, Klebsiella pneumoniae, and Pseudomonas aeruginosa. The evaluation shows that MiCId's workflow has a sensitivity value around 85% (with a lower bound at about 72%) and a precision greater than 95% in identifying antibiotic resistance proteins. In addition to having high sensitivity and precision, MiCId's workflow is fast and portable, making it a valuable tool for rapid identifications of bacteria as well as detection of their antibiotic resistance proteins. It performs microorganismal identifications, protein identifications, sample biomass estimates, and antibiotic resistance protein identifications in 6-17 min per MS/MS sample using computing resources that are available in most desktop and laptop computers. We have also demonstrated other use of MiCId's workflow. Using MS/MS data sets from samples of two bacterial clonal isolates, one being antibiotic-sensitive while the other being multidrug-resistant, we applied MiCId's workflow to investigate possible mechanisms of antibiotic resistance in these pathogenic bacteria; the results showed that MiCId's conclusions agree with the published study. The new version of MiCId (v.07.01.2021) is freely available for download at https://www.ncbi.nlm.nih.gov/CBBresearch/Yu/downloads.html.

Potential Use of Microbial Community Genomes in Various Dimensions of Agriculture Productivity and Its Management: A Review

Agricultural productivity is highly influenced by its associated microbial community. With advancements in omics technology, metagenomics is known to play a vital role in microbial world studies by unlocking the uncultured microbial populations present in the environment. Metagenomics is a diagnostic tool to target unique signature loci of plant and animal pathogens as well as beneficial microorganisms from samples. Here, we reviewed various aspects of metagenomics from experimental methods to techniques used for sequencing, as well as diversified computational resources, including databases and software tools. Exhaustive focus and study are conducted on the application of metagenomics in agriculture, deciphering various areas, including pathogen and plant disease identification, disease resistance breeding, plant pest control, weed management, abiotic stress management, post-harvest management, discoveries in agriculture, source of novel molecules/compounds, biosurfactants and natural product, identification of biosynthetic molecules, use in genetically modified crops, and antibiotic-resistant genes. Metagenomics-wide association studies study in agriculture on crop productivity rates, intercropping analysis, and agronomic field is analyzed. This article is the first of its comprehensive study and prospects from an agriculture perspective, focusing on a wider range of applications of metagenomics and its association studies.

Comparison and development of a metagenomic next-generation sequencing protocol for combined detection of DNA and RNA pathogens in cerebrospinal fluid

BACKGROUND

The purpose of this study was to evaluate different pretreatment, extraction, amplification, and library generation methods for metagenomic next-generation sequencing (mNGS) of cerebrospinal fluid (CSF) and to develop an efficient procedure for the simultaneous detection of DNA and RNA pathogens.

METHODS

We generated thirteen mock CSF samples with four representative pathogens of encephalitis. Each sample was subjected to ten different methods by varying sample pretreatment/nucleic acid extraction (microbial DNA, total DNA, total NA, total RNA, Whole Transcriptome Amplification (WTA)) and library generation (Illumina or NEB). Negative extraction controls (NECs) were used for each method variation.

RESULTS

We found that the quality of mNGS sequencing reads was higher from the NEB kit for library generation. Microbial DNA and total RNA increased microbial deposition by depleting the host DNA. Methods total NA and total RNA can detect gram-positive, gram-negative, RNA and DNA pathogens. We applied mNGS, including total NA and NEB library generation, to CSF samples from five patients diagnosed with infectious encephalitis and correctly determined all pathogens identified in clinical etiological tests.

CONCLUSIONS

Our findings suggested that total nucleic acid extraction combined with NEB library generation is the most effective mNGS procedure in CSF pathogen detection. The optimization of positive criteria and databases can improve the specificity and sensitivity of mNGS diagnosis.

TRIAL REGISTRATION

Chinese Clinical Trial Registry, ChiCTR1800015425 (29/03/2018), https://www.chictr.org.cn/edit.aspx?pid=26292&htm=4 .

Molecular characterization of the gastrointestinal eukaryotic virome in elderly people in Belem, Para, Brazil

Acute gastroenteritis is one of the main causes of mortality and morbidity worldwide, affecting mainly children, the immunocompromised and elderly people. Enteric viruses, especially rotavirus A, are considered important etiological agents, while long-term care facilities are considered favorable environments for the occurrence of sporadic cases and outbreaks of acute gastroenteritis. Therefore, it is important to monitor the viral agents present in nursing homes, especially because studies involving the elderly population in Brazil are scarce, resulting in a lack of available virological data. As a result, the causative agent remains unidentified in a large number of reported acute gastroenteritis cases. However, the advent of next-generation sequencing provides new opportunities for viral detection and discovery. The aim of this study was to identify the viruses that circulate among elderly people with and without acute gastroenteritis, living in residential care homes in Belém, Pará, Brazil, between 2017 and 2019. Ninety-three samples were collected and screened by immunochromatography and qPCR. After, the samples were analyzed individually or in pools by next generation sequencing to identify the viruses circulating in this population. In 26 sequenced samples, members of 13 eukaryotic virus families were identified. The most abundantly present virus families were Parvoviridae, Genomoviridae and Smacoviridae. Contigs displaying similarity to pegiviruses were also detected. Furthermore, a near-complete rotavirus A genome was obtained and could be classified as G3P[8] genotype with the equine DS-1-like genetic background. Complete sequences of the VP4 and VP7 genes of a rotavirus C were also detected, belonging to G4P[2]. This study demonstrates the first characterization of the gastrointestinal virome in elderly in Northern Brazil. A diversity of viruses was found to be present in patients with and without diarrhea, reinforcing the need to monitor elderly people residing in long-term care facilities, especially in cases of acute gastroenteritis.

Application of metagenomic sequencing toward rapid and sensitive diagnosis of goose avastrovirus infection in China

The gosling gout, a newly emerged disease, has widely broken out in China since 2017. Typical signs for the disease include diarrhea, anorexia, depression, dehydration, emaciation and paralysis. At autopsy, uratosis was the main pathological change which could be found at kidney, pericardium, air sac, muscle and leg joint. In this study, gosling gout was firstly diagnosed by metagenomic analysis. Samples of kidney, Fabricius bursa, spleen and jejunum were collected and submitted to next-generation DNA sequencing. Our results demonstrated that goose avastrovirus was highly related with this disease. We confirmed the sequencing results by reverse transcription polymerase chain reaction method and artificial infection experiment and got consistent results. In summary, metagenomic sequencing method combined with traditional molecular identification was applied toward diagnosis of a novel gosling gout disease in China and revealed that goose avastrovirus was highly related with this disease. It has been proved to be a powerful tool for rapid and sensitive diagnosis of animal diseases, especially for some exceptional pathogens. In addition, host range, variation, molecular pathogenesis and potential zoonotic infection of this novel goose astrovirus need to be further studied.

Metagenomics Approaches for Improving Food Safety: A Review

ABSTRACT

Advancements in next-generation sequencing technology have dramatically reduced the cost and increased the ease of microbial whole genome sequencing. This approach is revolutionizing the identification and analysis of foodborne microbial pathogens, facilitating expedited detection and mitigation of foodborne outbreaks, improving public health outcomes, and limiting costly recalls. However, next-generation sequencing is still anchored in the traditional laboratory practice of the selection and culture of a single isolate. Metagenomic-based approaches, including metabarcoding and shotgun and long-read metagenomics, are part of the next disruptive revolution in food safety diagnostics and offer the potential to directly identify entire microbial communities in a single food, ingredient, or environmental sample. In this review, metagenomic-based approaches are introduced and placed within the context of conventional detection and diagnostic techniques, and essential considerations for undertaking metagenomic assays and data analysis are described. Recent applications of the use of metagenomics for food safety are discussed alongside current limitations and knowledge gaps and new opportunities arising from the use of this technology.

HIGHLIGHTS

The Human Virome: Viral Metagenomics, Relations with Human Diseases, and Therapeutic Applications

The human body is colonized by a wide range of microorganisms. The field of viromics has expanded since the first reports on the detection of viruses via metagenomic sequencing in 2002. With the continued development of reference materials and databases, viral metagenomic approaches have been used to explore known components of the virome and discover new viruses from various types of samples. The virome has attracted substantial interest since the outbreak of the coronavirus disease 2019 (COVID-19) pandemic. Increasing numbers of studies and review articles have documented the diverse virome in various sites in the human body, as well as interactions between the human host and the virome with regard to health and disease. However, there have been few studies of direct causal relationships. Viral metagenomic analyses often lack standard references and are potentially subject to bias. Moreover, most virome-related review articles have focused on the gut virome and did not investigate the roles of the virome in other sites of the body in human disease. This review presents an overview of viral metagenomics, with updates regarding the relations between alterations in the human virome and the pathogenesis of human diseases, recent findings related to COVID-19, and therapeutic applications related to the human virome.

Metagenomic sequencing for detection and identification of the boxwood blight pathogen Calonectria pseudonaviculata

Pathogen detection and identification are key elements in outbreak control of human, animal, and plant diseases. Since many fungal plant pathogens cause similar symptoms, are difficult to distinguish morphologically, and grow slowly in culture, culture-independent, sequence-based diagnostic methods are desirable. Whole genome metagenomic sequencing has emerged as a promising technique because it can potentially detect any pathogen without culturing and without the need for pathogen-specific probes. However, efficient DNA extraction protocols, computational tools, and sequence databases are required. Here we applied metagenomic sequencing with the Oxford Nanopore Technologies MinION to the detection of the fungus Calonectria pseudonaviculata, the causal agent of boxwood (Buxus spp.) blight disease. Two DNA extraction protocols, several DNA purification kits, and various computational tools were tested. All DNA extraction methods and purification kits provided sufficient quantity and quality of DNA. Several bioinformatics tools for taxonomic identification were found suitable to assign sequencing reads to the pathogen with an extremely low false positive rate. Over 9% of total reads were identified as C. pseudonaviculata in a severely diseased sample and identification at strain-level resolution was approached as the number of sequencing reads was increased. We discuss how metagenomic sequencing could be implemented in routine plant disease diagnostics.

Seasonal and Technological Shifts of the WHO Priority Multi-Resistant Pathogens in Municipal Wastewater Treatment Plant and Its Receiving Surface Water: A Case Study

The present study was focused on the identification of multi-resistant bacteria from the WHO priority pathogens list in the samples taken from different stages of the full-scale municipal wastewater treatment plant and receiving water. Additionally, the seasonal variations of the selected multi-resistant pathogens were analyzed in the samples. In order to the aim of the study, the metagenomic DNA from the collected samples was isolated and sequenced. The samples were collected in three campaigns (spring, summer, autumn). Metagenomic DNA was isolated by the commercial kits, according to the manufacturer's instruction. Illumina sequencing system was employed, and the R program was used to metagenomic analysis. It was found that the wastewater samples and receiving water contained the multi-resistant bacteria from the WHO priority pathogens list. The seasonal and technological variations affected the distribution of the pathogens in the wastewater. No effect of the effluent on the pathogens in the receiving water was observed. The results indicated that antibiotic-resistant "priority pathogens" from the WHO list are there in the waste- and receiving water. Technological process and seasons effected their distribution in the environment. Metagenomic analysis can be used as sufficient tool in microbiological and human health risk assessment.

Evaluating the Prevalence of Foodborne Pathogens in Livestock Using Metagenomics Approach

Food safety is the most important global health issue due to foodborne pathogens after consumption of contaminated food. Foodborne bacteria such as Escherichia coli, Salmonella enterica, Staphylococcus aureus, Campylobacter spp., Bacillus cereus, Vibrio spp., Yersinia enterocolitica and Clostridium perfringens are leading causes of the majority of foodborne illnesses and deaths. These foodborne pathogens often come from the livestock feces, thus, we analyzed fecal microbial communities of three different livestock species to investigate the prevalence of foodborne pathogens in livestock feces using metagenomics analysis. Our data showed that alpha diversities of microbial communities were different according to livestock species. The microbial diversity of cattle feces was higher than that of chicken or pig feces. Moreover, microbial communities were significantly different among these three livestock species (cattle, chicken, and pig). At the genus level, Staphylococcus and Clostridium were found in all livestock feces, with chicken feces having higher relative abundances of Staphylococcus and Clostridium than cattle and pig feces. Genera Bacillus, Campylobacter, and Vibrio were detected in cattle feces. Chicken samples contained Bacillus, Listeria, and Salmonella with low relative abundance. Other genera such as Corynebacterium, Streptococcus, Neisseria, Helicobacter, Enterobacter, Klebsiella, and Pseudomonas known to be opportunistic pathogens were also detected in cattle, chicken, and pig feces. Results of this study might be useful for controlling the spread of foodborne pathogens in farm environments known to provide natural sources of these microorganisms.

Comparative hologenomics of two Ixodes scapularis tick populations in New Jersey

Tick-borne diseases, such as those transmitted by the blacklegged tick Ixodes scapularis, are a significant and growing public health problem in the US. There is mounting evidence that co-occurring non-pathogenic microbes can also impact tick-borne disease transmission. Shotgun metagenome sequencing enables sampling of the complete tick hologenome—the collective genomes of the tick and all of the microbial species contained therein, whether pathogenic, commensal or symbiotic. This approach simultaneously uncovers taxonomic composition and allows the detection of intraspecific genetic variation, making it a useful tool to compare spatial differences across tick populations. We evaluated this approach by comparing hologenome data from two tick samples (N = 6 ticks per location) collected at a relatively fine spatial scale, approximately 23 km apart, within a single US county. Several intriguing variants in the data between the two sites were detected, including polymorphisms in both in the tick’s own mitochondrial DNA and that of a rickettsial endosymbiont. The two samples were broadly similar in terms of the microbial species present, including multiple known tick-borne pathogens (Borrelia burgdorferi, Babesia microti, and Anaplasma phagocytophilum), filarial nematodes, and Wolbachia and Babesia species. We assembled the complete genome of the rickettsial endosymbiont (most likely Rickettsia buchneri) from both populations. Our results provide further evidence for the use of shotgun metagenome sequencing as a tool to compare tick hologenomes and differentiate tick populations across localized spatial scales.

Composition of Eukaryotic Viruses and Bacteriophages in Individuals with Acute Gastroenteritis

Metagenomics based on the next-generation sequencing (NGS) technique is a target-independent assay that enables the simultaneous detection and genomic characterization of all viruses present in a sample. There is a limited amount of data about the virome of individuals with gastroenteritis (GI). In this study, the enteric virome of 250 individuals (92% were children under 5 years old) with GI living in the northeastern and northern regions of Brazil was characterized. Fecal samples were subjected to NGS, and the metagenomic analysis of virus-like particles (VLPs) identified 11 viral DNA families and 12 viral RNA families. As expected, the highest percentage of viral sequences detected were those commonly associated with GI, including rotavirus, adenovirus, norovirus (94.8%, 82% and 71.2%, respectively). The most common co-occurrences, in a single individual, were the combinations of rotavirus-adenovirus, rotavirus-norovirus, and norovirus-adenovirus (78%, 69%, and 62%, respectively). In the same way, common fecal-emerging human viruses were also detected, such as parechovirus, bocaporvirus, cosavirus, picobirnavirus, cardiovirus, salivirus, and Aichivirus. In addition, viruses that infect plants, nematodes, fungi, protists, animals, and arthropods could be identified. A large number of unclassified viral contigs were also identified. We show that the metagenomics approach is a powerful and promising tool for the detection and characterization of different viruses in clinical GI samples.

A review of the resistome within the digestive tract of livestock

Antimicrobials have been widely used to prevent and treat infectious diseases and promote growth in food-production animals. However, the occurrence of antimicrobial resistance poses a huge threat to public and animal health, especially in less developed countries where food-producing animals often intermingle with humans. To limit the spread of antimicrobial resistance from food-production animals to humans and the environment, it is essential to have a comprehensive knowledge of the role of the resistome in antimicrobial resistance (AMR), The resistome refers to the collection of all antimicrobial resistance genes associated with microbiota in a given environment. The dense microbiota in the digestive tract is known to harbour one of the most diverse resistomes in nature. Studies of the resistome in the digestive tract of humans and animals are increasing exponentially as a result of advancements in next-generation sequencing and the expansion of bioinformatic resources/tools to identify and describe the resistome. In this review, we outline the various tools/bioinformatic pipelines currently available to characterize and understand the nature of the intestinal resistome of swine, poultry, and ruminants. We then propose future research directions including analysis of resistome using long-read sequencing, investigation in the role of mobile genetic elements in the expression, function and transmission of AMR. This review outlines the current knowledge and approaches to studying the resistome in food-producing animals and sheds light on future strategies to reduce antimicrobial usage and control the spread of AMR both within and from livestock production systems.

Metagenomic investigation of potential abortigenic pathogens in foetal tissues from Australian horses

BACKGROUND

Abortion in horses leads to economic and welfare losses to the equine industry. Most cases of equine abortions are sporadic, and the cause is often unknown. This study aimed to detect potential abortigenic pathogens in equine abortion cases in Australia using metagenomic deep sequencing methods.

RESULTS

After sequencing and analysis, a total of 68 and 86 phyla were detected in the material originating from 49 equine abortion samples and 8 samples from normal deliveries, respectively. Most phyla were present in both groups, with the exception of Chlamydiae that were only present in abortion samples. Around 2886 genera were present in the abortion samples and samples from normal deliveries at a cut off value of 0.001% of relative abundance. Significant differences in species diversity between aborted and normal tissues was observed. Several potential abortigenic pathogens were identified at a high level of relative abundance in a number of the abortion cases, including Escherichia coli, Klebsiella pneumoniae, Klebsiella oxytoca, Streptococcus equi subspecies zooepidemicus, Pantoea agglomerans, Acinetobacter lwoffii, Acinetobacter calcoaceticus and Chlamydia psittaci.

CONCLUSIONS

This work revealed the presence of several potentially abortigenic pathogens in aborted specimens. No novel potential abortigenic agents were detected. The ability to screen samples for multiple pathogens that may not have been specifically targeted broadens the frontiers of diagnostic potential. The future use of metagenomic approaches for diagnostic purposes is likely to be facilitated by further improvements in deep sequencing technologies.

Host-Microbe Metagenomics: a Lens To Refocus Our Perspective on Infectious and Inflammatory Diseases

A dynamic relationship involving pathogen, host immune response, and microbiome characterizes the biological framework of many infectious and inflammatory diseases. Combined host/microbe metagenomics (mNGS) enables simultaneous assessment of all three features, enabling the study and diagnosis of diverse infectious and inflammatory processes ranging from pneumonia to sepsis to inflammatory diseases such as rheumatoid arthritis. Host/microbe mNGS holds promise for new mechanistic insights, diagnostic approaches, and precision medicine interventions.

Misdiagnosed tuberculosis being corrected as Nocardia farcinica infection by metagenomic sequencing: a case report

Background

Disseminated nocardiosis is liable to be misdiagnosed owing to the non-specific clinical manifestations and laboratory/imaging findings. Metagenomic next-generation sequencing (mNGS) is a culture-independent and rapid method for direct identification of all microorganisms in clinical specimens.

Case presentation

A 72-year-old man was admitted to our hospital on February 20, 2019 with a history of recurrent cough, expectoration, fever, and diarrhea since 1 month, and unconsciousness since 1 week. Contrast-enhanced magnetic resonance imaging of head showed multiple lesions in the bilateral cerebral hemispheres, brainstem, and cerebellar hemispheres. The presumptive diagnosis was disseminated tuberculosis, although all tests for mycobacterium were negative. However, the patient did not benefit from antituberculosis treatment. Repeat MRI showed multiple abnormal signals in the brain and progression of meningeal thickening. Cerebrospinal fluid and bronchoalveolar lavage fluid specimens were subsequently sent for PMSeq metagenomics sequencing; the results indicated Nocardia. farcinica as the predominant pathogen. The anti-TB treatment was stopped and the patient was prescribed sulphamethoxazole in combination with linezolid and meropenem for nocardiosis. He showed gradual neurological improvement and was transferred to Huashan Hospital. He was discharged from the hospital on April 19, 2019, but died of persistent diarrhea on May 26, 2019.

Conclusions

Patients with suspected nocardiosis do not always respond to conventional treatment; therefore, mNGS can facilitate diagnosis and timely treatment decision-making.

Association between Ambient Temperature and Severe Diarrhoea in the National Capital Region, Philippines

Epidemiological studies have quantified the association between ambient temperature and diarrhoea. However, to our knowledge, no study has quantified the temperature association for severe diarrhoea cases. In this study, we quantified the association between mean temperature and two severe diarrhoea outcomes, which were mortality and hospital admissions accompanied with dehydration and/or co-morbidities. Using a 12-year dataset of three urban districts of the National Capital Region, Philippines, we modelled the non-linear association between weekly temperatures and weekly severe diarrhoea cases using a two-stage time series analysis. We computed the relative risks at the 95th (30.4 °C) and 5th percentiles (25.8 °C) of temperatures using minimum risk temperatures (MRTs) as the reference to quantify the association with high- and low-temperatures, respectively. The shapes of the cumulative associations were generally J-shaped with greater associations towards high temperatures. Mortality risks were found to increase by 53.3% [95% confidence interval (CI): 29.4%; 81.7%)] at 95th percentile of weekly mean temperatures compared with the MRT (28.2 °C). Similarly, the risk of hospitalised severe diarrhoea increased by 27.1% (95% CI: 0.7%; 60.4%) at 95th percentile in mean weekly temperatures compared with the MRT (28.6 °C). With the increased risk of severe diarrhoea cases under high ambient temperature, there may be a need to strengthen primary healthcare services and sustain the improvements made in water, sanitation, and hygiene, particularly in poor communities.

Surveillance of hemorrhagic fever and/or neuroinvasive disease: challenges of diagnosis

OBJECTIVE

To evaluate the performance of post mortem laboratory analysis in identifying the causes of hemorrhagic fever and/or neuroinvasive disease in deaths by arbovirus infection.

METHODS

Retrospective cross-sectional study based on the differential analysis and final outcome obtained in patients whose samples underwent laboratory testing for arboviruses at the Pathology Center of the Adolfo Lutz Institute, in São Paulo, Brazil.

RESULTS

Of the 1355 adults clinically diagnosed with hemorrhagic fever and/or neuroinvasive disease, the most commonly attributed cause of death and the most common final outcome was dengue fever. Almost half of the samples tested negative on all laboratory tests conducted.

CONCLUSION

The failure to identify the causative agent in a great number of cases highlights a gap in the diagnosis of deaths of unknown etiology. Additional immunohistochemical and molecular assessments need to be added to the post-mortem protocol if all laboratory evaluations performed fail to identify a causative agent. While part of our findings may be due to technical issues related to sample fixation, better information availability when making the initial diagnosis is crucial. Including molecular approaches might lead to a significant advancement in diagnostic accuracy.

A review on application of next-generation sequencing methods for profiling of protozoan parasites in water: Current methodologies, challenges, and perspectives

The advancement in metagenomic techniques has provided novel tools for profiling human parasites in environmental matrices, such as water and wastewater. However, application of metagenomic techniques for the profiling of protozoan parasites in environmental matrices is not commonly reported in the literature. The key factors leading to the less common use of metagenomics are the complexity and large eukaryotic genome, the prevalence of small parasite populations in environmental samples compared to bacteria, difficulties in extracting DNA from (oo)cysts, and limited reference databases for parasites. This calls for further research to develop optimized methods specifically looking at protozoan parasites in the environment. This study reviews the current workflow, methods and provide recommendations for the standardization of techniques. The article identifies and summarizes the key methods, advantages, and limitations associated with metagenomic analysis, like sample pre-processing, DNA extraction, sequencing approaches, and analysis methods. The study enhances the understanding and application of standardized protocols for profiling of protozoan parasite community from highly complexe samples and further creates a resourceful comparison among datasets without any biases.

Next Generation High Throughput Sequencing to Assess Microbial Communities: An Application Based on Water Quality

Traditional techniques to identify different contaminants (biological or chemical) in the waters are slow, laborious, and can require specialized expertise. Hence, the rapid determination of water quality using more sensitive and reliable metagenomic based approaches attains special importance. Metagenomics deals with the study of genetic material that is recovered from microbial communities present in environmental samples. In traditional techniques cultivation-based methodologies were used to describe the diversity of microorganisms in environmental samples. It has failed to function as a robust marker because of limited taxonomic and phylogenetic implications. In this backdrop, high-throughput DNA sequencing approaches have proven very powerful in microbial source tracking because of investigating the full variety of genome-based analysis such as microbial genetic diversity and population structure played by them. Next generation sequencing technologies can reveal a greater proportion of microbial communities that have not been reported earlier by traditional techniques. The present review highlights the shift from traditional techniques for the basic study of community composition to next-generation sequencing (NGS) platforms and their potential applications to the biomonitoring of water quality in relation to human health.

Metagenomics Approaches to Investigate the Gut Microbiome of COVID-19 Patients

Over the last decade, it has become increasingly apparent that the microbiome is a central component in human well-being and illness. However, to establish innovative therapeutic methods, it is crucial to learn more about the microbiota. Thereby, the area of metagenomics and associated bioinformatics methods and tools has become considerable in the study of the human microbiome biodiversity. The application of these metagenomics approaches to studying the gut microbiome in COVID-19 patients could be one of the promising areas of research in the fight against the SARS-CoV-2 infection and disparity. Therefore, understanding how the gut microbiome is affected by or could affect the SARS-CoV-2 is very important. Herein, we present an overview of approaches and methods used in the current published studies on COVID-19 patients and the gut microbiome. The accuracy of these researches depends on the appropriate choice and the optimal use of the metagenomics bioinformatics platforms and tools. Interestingly, most studies reported that COVID-19 patients' microbiota are enriched with opportunistic microorganisms. The choice and use of appropriate computational tools and techniques to accurately investigate the gut microbiota is therefore critical in determining the appropriate microbiome profile for diagnosis and the most reliable antiviral or preventive microbial composition.

Metagenomics: preventing future pandemics

Metagenomic approaches have been key to successful tracing and outbreak management during the COVID-19 pandemic. How can we use this knowledge to better prepare, strategize and prevent future pandemics? [Formula: see text].