Next-generation sequencing (NGS) has revolutionized clinical microbiology, particularly in diagnosing respiratory infectious diseases and conducting epidemiological investigations. This narrative review summarizes conventional methods for routine respiratory infection diagnosis, including culture, smear microscopy, immunological assays, image techniques as well as polymerase chain reaction(PCR). In contrast to conventional methods, there is a new detection technology, sequencing technology, and here we mainly focus on the next-generation sequencing NGS, especially metagenomic NGS(mNGS). NGS offers significant advantages over traditional methods. Firstly, mNGS eliminates assumptions about pathogens, leading to faster and more accurate results, thus reducing diagnostic time. Secondly, it allows unbiased identification of known and novel pathogens, offering broad-spectrum coverage. Thirdly, mNGS not only identifies pathogens but also characterizes microbiomes, analyzes human host responses, and detects resistance genes and virulence factors. It can complement targeted sequencing for bacterial and fungal classification. Unlike traditional methods affected by antibiotics, mNGS is less influenced due to the extended survival of pathogen DNA in plasma, broadening its applicability. However, barriers to full integration into clinical practice persist, primarily due to cost constraints and limitations in sensitivity and turnaround time. Despite these challenges, ongoing advancements aim to improve cost-effectiveness and efficiency, making NGS a cornerstone technology for global respiratory infection diagnosis.

Lung cancer is an exceedingly malignant tumor reported as having the highest morbidity and mortality of any cancer worldwide, thus posing a great threat to global health. Despite the growing demand for precision medicine, current methods for early clinical detection, treatment and prognosis monitoring in lung cancer are hampered by certain bottlenecks. Studies have found that during the formation and development of a tumor, molecular substances carrying tumor-related genetic information can be released into body fluids. Liquid biopsy (LB), a method for detecting these tumor-related markers in body fluids, maybe a way to make progress in these bottlenecks. In recent years, LB technology has undergone rapid advancements. Therefore, this review will provide information on technical updates to LB and its potential clinical applications, evaluate its effectiveness for specific applications, discuss the existing limitations of LB, and present a look forward to possible future clinical applications. Specifically, this paper will introduce technical updates from the prospectives of engineering breakthroughs in the detection of membrane-based LB biomarkers and other improvements in sequencing technology. Additionally, it will summarize the latest applications of liquid biopsy for the early detection, diagnosis, treatment, and prognosis of lung cancer. We will present the interconnectedness of clinical and laboratory issues and the interplay of technology and application in LB today.

UNASSIGNED: A comprehensive strategy for microbial identification and contamination investigation during sterile drug manufacturing was innovatively established in this study, mainly based on MALDI-TOF MS for the identification and complemented by sequencing technology on strain typing.
UNASSIGNED: It was implemented to monitor the bacterial contamination of a sterile drug manufacturing facility, including its bacterial distribution features and patterns. In three months, two hundred ninety-two samples were collected covering multiple critical components of raw materials, personnel, environment, and production water.
UNASSIGNED: Based on our strategy, the bacterial profile across the production process was determined: 241/292 bacterial identities were obtained, and Staphylococcus spp. (40.25%), Micrococcus spp.(11.20%), Bacillus spp. (8.30%), Actinobacteria (5.81%), and Paenibacillus spp. (4.56%) are shown to be the most dominant microbial contaminants. With 75.8% species-level and 95.4% genus-level identification capability, MALDI-TOF MS was promising to be a first-line tool for environmental monitoring routine. Furthermore, to determine the source of the most frequently occurring Staphylococcus cohnii, which evidenced a widespread presence in the entire process, a more discriminating S. cohnii whole-genome SNP typing method was developed to track the transmission routes. Phylogenetic analysis based on SNP results indicated critical environment contamination is highly relevant to personnel flow in this case. The strain typing results provide robust and accurate information for the following risk assessment step and support effective preventive and corrective measures.
UNASSIGNED: In general, the strategy presented in this research will facilitate the development of improved production and environmental control processes for the pharmaceutical industry, and give insights about how to provide more sound and reliable evidence for the optimization of its control program.

Introduction: We have previously observed phenotypic and developmental changes upon the ectopic expression of the RUNX3 or the ZBTB46 transcription factors in mouse embryonic stem cell (ESC) derived progenitors. In this study, we evaluated the gene expression profiles of the RUNX3- and the ZBTB46-instructed murine ESCs with RNA-seq testing two next-generation sequencing technologies. Methods: We compared the DNA nanoball-based DNBSEQ G400 sequencer (MGI) with the bridge-PCR-based NextSeq 500 instrument (Illumina) for RNA sequencing. Moreover, we also compared two types of MGI sequencing reagents (Standard versus Hot-massive parallel sequencing (MPS)) with the DNBSEQ G400. Results: We observed that both sequencing platforms showed comparable levels of quality, sequencing uniformity, and gene expression profiles. For example, highly overlapping RUNX3- and ZBTB46-regulated gene lists were obtained from both sequencing datasets. Moreover, we observed that the Standard and the Hot-MPS-derived RUNX3- and ZBTB46-regulated gene lists were also considerably overlapped. This transcriptome analysis also helped us to identify differently expressed genes in the presence of the transgenic RUNX3 or ZBTB46. For example, we found that Gzmb, Gzmd, Gzme, Gdf6, and Ccr7 genes were robustly upregulated upon the forced expression of Runx3; on the other hand, Gpx2, Tdpoz4, and Arg2 were induced alongside the ectopic expression of Zbtb46. Discussion: Similar gene expression profile and greatly overlapping RUNX3- and ZBTB46-regulated gene sets were detected with both DNA sequencing platforms. Our analyses demonstrate that both sequencing technologies are suitable for transcriptome profiling and target gene selection. These findings suggest that DNBSEQ G400 represents a cost-effective alternative sequencing platform for gene expression monitoring. Moreover, this analysis provides a resource for exploration of the RUNX3- and ZBTB46-dependent gene regulatory networks.

With the advancements in gene sequencing technologies, including genome-wide association studies, polygenetic risk scores, and high-throughput sequencing, there has been a tremendous advantage in mapping a detailed blueprint for the genetic model of bipolar disorder (BD). To date, intriguing genetic clues have been identified to explain the development of BD, as well as the genetic association that might be applied for the development of susceptibility prediction and pharmacogenetic intervention. Risk genes of BD, such as CACNA1C, ANK3, TRANK1, and CLOCK, have been found to be involved in various pathophysiological processes correlated with BD. Although the specific roles of these genes have yet to be determined, genetic research on BD will help improve the prevention, therapeutics, and prognosis in clinical practice. The latest preclinical and clinical studies, and reviews of the genetics of BD, are analyzed in this review, aiming to summarize the progress in this intriguing field and to provide perspectives for individualized, precise, and effective clinical practice.

Genomic benchmark datasets are essential to driving the field of genomics and bioinformatics. They provide a snapshot of the performances of sequencing technologies and analytical methods and highlight future challenges. However, they depend on sequencing technology, reference genome, and available benchmarking methods. Thus, creating a genomic benchmark dataset is laborious and highly challenging, often involving multiple sequencing technologies, different variant calling tools, and laborious manual curation. In this review, we discuss the available benchmark datasets and their utility. Additionally, we focus on the most recent benchmark of genes with medical relevance and challenging genomic complexity.

Over the past 20 years, tremendous advances in sequencing technologies and computational algorithms have spurred plant genomic research into a thriving era with hundreds of genomes decoded already, ranging from those of nonvascular plants to those of flowering plants. However, complex plant genome assembly is still challenging and remains difficult to fully resolve with conventional sequencing and assembly methods due to high heterozygosity, highly repetitive sequences, or high ploidy characteristics of complex genomes. Herein, we summarize the challenges of and advances in complex plant genome assembly, including feasible experimental strategies, upgrades to sequencing technology, existing assembly methods, and different phasing algorithms. Moreover, we list actual cases of complex genome projects for readers to refer to and draw upon to solve future problems related to complex genomes. Finally, we expect that the accurate, gapless, telomere-to-telomere, and fully phased assembly of complex plant genomes could soon become routine.

Soil microorganisms play an indispensable role in plant growth and are widely used to promote plant growth. However, poor microbial strains are homogeneous. The heavy application of chemical fertilizers and pesticides to agricultural soil has adversely affected the soil flora, necessitating the regulation of the soil flora to maintain soil health. In this study, X-45, a highly efficient and phosphorus-dissolving strain of the lysogenic bacterium Serratia marcescens N1.14 was isolated from bare rock slope soil samples from Yueyang Avenue, Hunan Province, China. We observed that microbial strain X-45 could release P from the rocks into solution when the sample rocks were used as the only phosphorus source. Furthermore, we observed that the P content in media increased by 3.08 X compared to the control. After applying X-45 as a bacterial fertilizer, the growth of potted Indigofera pseudotinctoria plants significantly increased, the soil physicochemical properties were significantly improved, and the relative abundance of Bradyrhizobium in the soil increased significantly from 1 to 42%. Besides, Bradyrhizobium became the most dominant genus in the soil. The indirect promotion of another beneficial microorganism by X-45 further revealed the intrinsic mechanism by which X-45 exerted its effect on plant promotion and soil improvement. Using this bacteria, the hypothesis of the superposition effect of legume plant promotion was also confirmed.

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Microbial-assisted phytoremediation promotes the ecological restoration of high and steep rocky slopes. To determine the structure and function of microbial communities in the soil in response to changes in soil nutrient content, the bacterial communities of rhizospheric soil from three types of plants, i.e., Robinia pseudoacacia, Pinus massoniana, and Cynodon dactylon, were analyzed using Illumina sequencing technology. High-quality sequences were clustered at the 97% similarity level. The dominant genera were found to be RB41, Gemmatimonas, Sphingomonas, Bradyrhizobium, and Ellin6067. The Tukey HSD (honestly significant difference) test results showed that the abundance of RB41 and Gemmatimonas were significantly different among three types of plants (p < 0.01). The relative abundances of RB41 (13.32%) and Gemmatimonas (3.36%) in rhizospheric soil samples from R. pseudoacacia were significantly higher than that from P. massoniana (0.16 and 0.35%) and C. dactylon (0.40 and 0.82%), respectively. The soil chemical properties analyses suggested that significant differences in rhizospheric soil nutrient content among the three plant types. Especially the available phosphorus, the content of it in the rhizospheric soil of R. pseudoacacia was about 280% (P. massoniana) and 58% (C. dactylon) higher than that of the other two plants, respectively. The soil bacterial communities were further studied using the correlation analysis and the Tax4Fun analysis. A significant and positive correlation was observed between Gemmatimonas and soil nutrient components. Except total nitrogen, the positive correlation between Gemmatimonas and other soil nutrient components was above 0.9. The outcomes of these analyses suggested that Gemmatimonas could be the indicator genus in response to changes in the soil nutrient content. Besides, the genes involved in metabolism were the major contributor to soil nutrients. This study showed that soil nutrients affect the soil bacterial community structure and function. In addition, pot experiments showed that Microbacterium invictum X-18 isolated from the rhizospheric soil of R. pseudoacacia significantly improved soil nutrient content and increased R. pseudoacacia growth. A significant increase in the numbers of nodules of R. pseudoacacia and an increase of 28% in plant height, accompanied by an increase of 94% in available phosphorus was measured in the M. invictum X-18 treatment than the control treatment.