A systematic sequencing-based approach for microbial contaminant detection and functional inference

Transcriptomic Reprogramming and Genetic Variations Contribute to Western Hemlock Defense and Resistance Against Annosus Root and Butt Rot Disease

Western hemlock (Tsuga heterophylla) is highly susceptible to Annosus root and butt rot disease, caused by Heterobasidion occidentale across its native range in western North America. Understanding molecular mechanisms of tree defense and dissecting genetic components underlying disease resistance will facilitate forest breeding and disease control management. The aim of this study was to profile host transcriptome reprogramming in response to pathogen infection using RNA-seq analysis. Inoculated seedlings were clearly grouped into three types: quantitative resistant (QR), susceptible (Sus), and un-infected (Uif), based on profiles of H. occidentale genes expressed in host tissues. Following de novo assembly of a western hemlock reference transcriptome with more than 33,000 expressed genes, the defensive transcriptome reprogramming was characterized and a set of differentially expressed genes (DEGs) were identified with gene ontology (GO) annotation. The QR seedlings showed controlled and coordinated molecular defenses against biotic stressors with enhanced biosynthesis of terpenoids, cinnamic acids, and other secondary metabolites. The Sus seedlings showed defense responses to abiotic stimuli with a few biological processes enhanced (such as DNA replication and cell wall organization), while others were suppressed (such as killing of cells of other organism). Furthermore, non-synonymous single nucleotide polymorphisms (ns-SNPs) of the defense- and resistance-related genes were characterized with high genetic variability. Both phylogenetic analysis and principal coordinate analysis (PCoA) revealed distinct evolutionary distances among the samples. The QR and Sus seedlings were well separated and grouped into different phylogenetic clades. This study provides initial insight into molecular defense and genetic components of western hemlock resistance against the Annosus root and butt rot disease. Identification of a large number of genes and their DNA variations with annotated functions in plant resistance and defense promotes the development of genomics-based breeding strategies for improved western hemlock resistance to H. occidentale.

CleanSeq: A Pipeline for Contamination Detection, Cleanup, and Mutation Verifications from Microbial Genome Sequencing Data

Contaminations frequently occur in bacterial cultures, which significantly affect the reproducibility and reliability of the results from whole-genome sequencing (WGS). Decontaminated WGS data with clean reads is the only desirable source for detecting possible variants correctly. Improvements in bioinformatics are essential to analyze the contaminated WGS dataset. Existing pipelines usually contain contamination detection, decontamination, and variant calling separately. The efficiency and results from existing pipelines fluctuate since distinctive computational models and parameters are applied. It is then promising to develop a bioinformatical tool containing functions to discriminate and remove contaminated reads and improve variant calling from clean reads. In this study, we established a Python-based pipeline named CleanSeq for automatic detection and removal of contaminating reads, analyzing possible genome variants with proper verifications via local re-alignments. The application and reproducibility are proven in either simulated, publicly available datasets or actual genome sequencing reads from our experimental evolution study in Escherichia coli. We successfully obtained decontaminated reads, called out all seven consistent mutations from the contaminated bacterial sample, and derived five colonies. Collectively, the results demonstrated that CleanSeq could effectively process the contaminated samples to achieve decontaminated reads, based on which reliable results (i.e., variant calling) could be obtained.

Another lesson from unmapped reads: in-depth analysis of RNA-Seq reads from various horse tissues

In recent years, a vast amount of sequencing data has been generated and large improvements have been made to reference genome sequences. Despite these advances, significant portions of reads still do not map to reference genomes and these reads have been considered as junk or artificial sequences. Recent studies have shown that these reads can be useful, e.g., for refining reference genomes or detecting contaminating microorganisms present in the analyzed biological samples. A special case of this is RNA sequencing (RNA-Seq) reads that come from tissue transcriptomes. Unmapped reads from RNA-Seq have received much less attention than those from whole-genome sequencing. In particular, in the horse, an analysis of unmapped RNA reads has not been performed yet. Thus, in this study, we analyzed the unmapped reads originating from the RNA-Seq performed through the Functional Annotation of Animal Genomes (FAANG) project in the horse, using eight different tissues from two mares. We demonstrated that unmapped reads from RNA-Seq could be easily assembled into transcripts relating to many important genes present in the sequences of other mammals. Large portions of these transcripts did not have coding potential and, thus, can be considered as non-coding RNA. Moreover, reads that were not mapped to the reference genome but aligned to the entries in NCBI database of horse proteins were enriched for biological processes that largely correspond to the functions of organ from which RNA was isolated and thus are presumably true transcripts of genes associated with cell metabolism in those tissues. In addition, a portion of reads aligned to the common pathogenic or neutral microbiota, of which the most common was Brucella spp. These data suggest that unmapped reads can be an important target for in-depth analysis that may substantially enrich results of initial RNA-Seq experiments for various tissues and organs.

FastViFi: Fast and accurate detection of (Hybrid) Viral DNA and RNA

DNA viruses are important infectious agents known to mediate a large number of human diseases, including cancer. Viral integration into the host genome and the formation of hybrid transcripts are also associated with increased pathogenicity. The high variability of viral genomes, however requires the use of sensitive ensemble hidden Markov models that add to the computational complexity, often requiring > 40 CPU-hours per sample. Here, we describe FastViFi, a fast 2-stage filtering method that reduces the computational burden. On simulated and cancer genomic data, FastViFi improved the running time by 2 orders of magnitude with comparable accuracy on challenging data sets. Recently published methods have focused on identification of location of viral integration into the human host genome using local assembly, but do not extend to RNA. To identify human viral hybrid transcripts, we additionally developed ensemble Hidden Markov Models for the Epstein Barr virus (EBV) to add to the models for Hepatitis B (HBV), Hepatitis C (HCV) viruses and the Human Papillomavirus (HPV), and used FastViFi to query RNA-seq data from Gastric cancer (EBV) and liver cancer (HBV/HCV). FastViFi ran in <10 minutes per sample and identified multiple hybrids that fuse viral and human genes suggesting new mechanisms for oncoviral pathogenicity. FastViFi is available at https://github.com/sara-javadzadeh/FastViFi.

Metagenomics-enabled microbial surveillance

Lessons learnt from the COVID-19 pandemic include increased awareness of the potential for zoonoses and emerging infectious diseases that can adversely affect human health. Although emergent viruses are currently in the spotlight, we must not forget the ongoing toll of morbidity and mortality owing to antimicrobial resistance in bacterial pathogens and to vector-borne, foodborne and waterborne diseases. Population growth, planetary change, international travel and medical tourism all contribute to the increasing frequency of infectious disease outbreaks. Surveillance is therefore of crucial importance, but the diversity of microbial pathogens, coupled with resource-intensive methods, compromises our ability to scale-up such efforts. Innovative technologies that are both easy to use and able to simultaneously identify diverse microorganisms (viral, bacterial or fungal) with precision are necessary to enable informed public health decisions. Metagenomics-enabled surveillance methods offer the opportunity to improve detection of both known and yet-to-emerge pathogens.

Mycoplasma decontamination in Chlamydia trachomatis culture: a curative approach

Mycoplasma contamination of cell culture represents a serious problem in research and decontamination from cell-propagated obligate intracellular bacteria has proven challenging. Here, we presented an optimized protocol to remove Mycoplasma from contaminated Chlamydia trachomatis culture. A stepwise procedure of Mycoplasma removal entails (i) incubation in nonionic detergent containing solution, and (ii) separation of viable chlamydial organisms by fluorescence-activated cell sorting (FACS), followed by subcloning using a focus-forming assay. We also adapted a polymerase chain reaction (PCR) assay using paired universal and Mycoplasma-specific primers, which are distinguishable from the C. trachomatis counterparts, in combination with Sanger sequencing to determine the presence of mycoplasmas' 16S rRNA genes. These integrated approaches allow for full removal of Mycoplasma, as verified by the improved PCR assay, without compromising the capacity of viable C. trachomatis to adapt to new infection in epithelial cells. Some pitfalls during the Mycoplasma decontamination process are discussed.

Plant Growth-Promoting Bacteria as an Emerging Tool to Manage Bacterial Rice Pathogens

As a major food crop, rice (Oryza sativa) is produced and consumed by nearly 90% of the population in Asia with less than 9% produced outside Asia. Hence, reports on large scale grain losses were alarming and resulted in a heightened awareness on the importance of rice plants' health and increased interest against phytopathogens in rice. To serve this interest, this review will provide a summary on bacterial rice pathogens, which can potentially be controlled by plant growth-promoting bacteria (PGPB). Additionally, this review highlights PGPB-mediated functional traits, including biocontrol of bacterial rice pathogens and enhancement of rice plant's growth. Currently, a plethora of recent studies address the use of PGPB to combat bacterial rice pathogens in an attempt to replace existing methods of chemical fertilizers and pesticides that often lead to environmental pollutions. As a tool to combat bacterial rice pathogens, PGPB presented itself as a promising alternative in improving rice plants' health and simultaneously controlling bacterial rice pathogens in vitro and in the field/greenhouse studies. PGPB, such as Bacillus, Pseudomonas, Enterobacter, Streptomyces, are now very well-known. Applications of PGPB as bioformulations are found to be effective in improving rice productivity and provide an eco-friendly alternative to agroecosystems.

Application prospects of cerebrospinal fluid DIA techniques in identifying key regulatory molecules for mental disorders in encephalitis

At present, data independent acquisition (DIA) protein spectrum detection technology is one of the most attractive mass spectrometry acquisition techniques, which once led the new development of quantitative proteomics. Its application fields include the screening of clinical disease markers, the study of action mechanism, the study of drug targets and so on. DIA has been wide-ranging used in clinic because of its high throughput, high resolution and high reproducibility. The occurrence of mental disorders in encephalitis is common, and such neurocognitive impairment has a dramatically impact on the disease progression and prognosis of patients, which undoubtedly increases the economic burden of sufferers' families and society. Under the circumstance that the mechanism of mental disorder of encephalitis is still unknown, this paper summarizes a large number of literatures of encephalitis, originates the possibility of the application of cerebrospinal fluid detection by DIA in the occurrence of mental disorder of encephalitis, seeks for biomarkers for the occurrence of mental disorder of encephalitis, and provides clinical guidance.

OpenContami: a web-based application for detecting microbial contaminants in next-generation sequencing data

SUMMARY

Microorganisms infect and contaminate eukaryotic cells during the course of biological experiments. Because microbes influence host cell biology and may therefore lead to erroneous conclusions, a computational platform that facilitates decontamination is indispensable. Recent studies show that next-generation sequencing (NGS) data can be used to identify the presence of exogenous microbial species. Previously, we proposed an algorithm to improve detection of microbes in NGS data. Here, we developed an online application, OpenContami, which allows researchers easy access to the algorithm via interactive web-based interfaces. We have designed the application by incorporating a database comprising analytical results from a large-scale public dataset and data uploaded by users. The database serves as a reference for assessing user data and provides a list of genera detected from negative blank controls as a 'blacklist', which is useful for studying human infectious diseases. OpenContami offers a comprehensive overview of exogenous species in NGS datasets; as such, it will increase our understanding of the impact of microbial contamination on biological and pathological traits.

AVAILABILITY AND IMPLEMENTATION

OpenContami is freely available at: https://openlooper.hgc.jp/opencontami/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Sonochemical coating of Prussian Blue for the production of smart bacterial-sensing hospital textiles

In healthcare facilities, environmental microbes are responsible for numerous infections leading to patient's health complications and even death. The detection of the pathogens present on contaminated surfaces is crucial, although not always possible with current microbial detection technologies requiring sample collection and transfer to the laboratory. Based on a simple sonochemical coating process, smart hospital fabrics with the capacity to detect live bacteria by a simple change of colour are presented here. Prussian Blue nanoparticles (PB-NPs) are sonochemically coated on polyester-cotton textiles in a single-step requiring 15 min. The presence of PB-NPs confers the textile with an intensive blue colour and with bacterial-sensing capacity. Live bacteria in the textile metabolize PB-NPs and reduce them to colourless Prussian White (PW), enabling in situ detection of bacterial presence in less than 6 h with the bare eye (complete colour change requires 40 h). The smart textile is sensitive to both Gram-positive and Gram-negative bacteria, responsible for most nosocomial infections. The redox reaction is completely reversible and the textile recovers its initial blue colour by re-oxidation with environmental oxygen, enabling its re-use. Due to its simplicity and versatility, the current technology can be employed in different types of materials for control and prevention of microbial infections in hospitals, industries, schools and at home.