A new long-read mitochondrial-genome protocol (PacBio HiFi) for haemosporidian parasites: a tool for population and biodiversity studies.

BACKGROUND: Studies on haemosporidian diversity, including origin of human malaria parasites, malaria's zoonotic dynamic, and regional biodiversity patterns, have used target gene approaches. However, current methods have a trade-off between scalability and data quality. Here, a long-read Next-Generation Sequencing protocol using PacBio HiFi is presented. The data processing is supported by a pipeline that uses machine-learning for analysing the reads. METHODS: A set of primers was designed to target approximately 6 kb, almost the entire length of the haemosporidian mitochondrial genome. Amplicons from different samples were multiplexed in an SMRTbell® library preparation. A pipeline (HmtG-PacBio Pipeline) to process the reads is also provided; it integrates multiple sequence alignments, a machine-learning algorithm that uses modified variational autoencoders, and a clustering method to identify the mitochondrial haplotypes/species in a sample. Although 192 specimens could be studied simultaneously, a pilot experiment with 15 specimens is presented, including in silico experiments where multiple data combinations were tested. RESULTS: The primers amplified various haemosporidian parasite genomes and yielded high-quality mt genome sequences. This new protocol allowed the detection and characterization of mixed infections and co-infections in the samples. The machine-learning approach converged into reproducible haplotypes with a low error rate, averaging 0.2% per read (minimum of 0.03% and maximum of 0.46%). The minimum recommended coverage per haplotype is 30X based on the detected error rates. The pipeline facilitates inspecting the data, including a local blast against a file of provided mitochondrial sequences that the researcher can customize. CONCLUSIONS: This is not a diagnostic approach but a high-throughput method to study haemosporidian sequence assemblages and perform genotyping by targeting the mitochondrial genome. Accordingly, the methodology allowed for examining specimens with multiple infections and co-infections of different haemosporidian parasites. The pipeline enables data quality assessment and comparison of the haplotypes obtained to those from previous studies. Although a single locus approach, whole mitochondrial data provide high-quality information to characterize species pools of haemosporidian parasites.

Genomic profiling of pleomorphic rhabdomyosarcoma reveals a genomic signature distinct from that of embryonal rhabdomyosarcoma.

Pleomorphic rhabdomyosarcoma (PRMS) is a rare and highly aggressive sarcoma, occurring mostly in the deep soft tissues of middle-aged adults and showing a variable degree of skeletal muscle differentiation. The diagnosis is challenging as pathologic features overlap with embryonal rhabdomyosarcoma (ERMS), malignant Triton tumor, and other pleomorphic sarcomas. As recurrent genetic alterations underlying PRMS have not been described to date, ancillary molecular diagnostic testing is not useful in subclassification. Herein, we perform genomic profiling of a well-characterized cohort of 14 PRMS, compared to a control group of 23 ERMS and other pleomorphic sarcomas (undifferentiated pleomorphic sarcoma and pleomorphic liposarcoma) using clinically validated DNA-targeted Next generation sequencing (NGS) panels (MSK-IMPACT). The PRMS cohort included eight males and six females, with a median age of 53 years (range 31-76 years). Despite similar tumor mutation burdens, the genomic landscape of PRMS, with a high frequency of TP53 (79%) and RB1 (43%) alterations, stood in stark contrast to ERMS, with 4% and 0%, respectively. CDKN2A deletions were more common in PRMS (43%), compared to ERMS (13%). In contrast, ERMS harbored somatic driver mutations in the RAS pathway and loss of function mutations in BCOR, which were absent in PRMS. Copy number variations in PRMS showed multiple chromosomal arm-level changes, most commonly gains of chr17p and chr22q and loss of chr6q. Notably, gain of chr8, commonly seen in ERMS (61%) was conspicuously absent in PRMS. The genomic profiles of other pleomorphic sarcomas were overall analogous to PRMS, showing shared alterations in TP53, RB1, and CDKN2A. Overall survival and progression-free survival of PRMS were significantly worse (p < 0.0005) than that of ERMS. Our findings revealed that the molecular landscape of PRMS aligns with other adult pleomorphic sarcomas and is distinct from that of ERMS. Thus, NGS assays may be applied in select challenging cases toward a refined classification. Finally, our data corroborate the inclusion of PRMS in the therapeutic bracket of pleomorphic sarcomas, given that their clinical outcomes are comparable.

HPV genotyping in clinical samples using long-read single-molecule real-time sequencing.

Human papillomavirus (HPV) genotyping is widely used, particularly in combination with high-risk (HR) HPV tests for cervical cancer screening. We developed a genotyping method using sequences of approximately 800 bp in the E6/E7 region obtained by PacBio single molecule real-time sequencing (SMRT) and evaluated its performance against MY09-11 L1 sequencing and after the APTIMA HPV genotyping assay. The levels of concordance of PacBio E6/E7 SMRT sequencing with MY09-11 L1 sequencing and APTIMA HPV genotyping were 100% and 90.8%, respectively. The sensitivity of PacBio E6/EA7 SMRT was slightly greater than that of L1 sequencing and, as expected, lower than that of HR-HPV tests. In the context of cervical cancer screening, PacBio E6/E7 SMRT is then best used after a positive HPV test. PacBio E6/E7 SMRT genotyping is an attractive alternative for HR and LR-HPV genotyping of clinical samples. PacBio SMRT sequencing provides unbiased genotyping and can detect multiple HPV infections and haplotypes within a genotype.

Untacking small RNA profiling and RNA fragment footprinting: Approaches and challenges in library construction.

Small RNAs (sRNAs) with sizes ranging from 15 to 50 nucleotides (nt) are critical regulators of gene expression control. Prior studies have shown that sRNAs are involved in a broad range of biological processes, such as organ development, tumorigenesis, and epigenomic regulation; however, emerging evidence unveils a hidden layer of diversity and complexity of endogenously encoded sRNAs profile in eukaryotic organisms, including novel types of sRNAs and the previously unknown post-transcriptional RNA modifications. This underscores the importance for accurate, unbiased detection of sRNAs in various cellular contexts. A multitude of high-throughput methods based on next-generation sequencing (NGS) are developed to decipher the sRNA expression and their modifications. Nonetheless, distinct from mRNA sequencing, the data from sRNA sequencing suffer frequent inconsistencies and high variations emanating from the adapter contaminations and RNA modifications, which overall skew the sRNA libraries. Here, we summarize the sRNA-sequencing approaches, and discuss the considerations and challenges for the strategies and methods of sRNA library construction. The pros and cons of sRNA sequencing have significant implications for implementing RNA fragment footprinting approaches, including CLIP-seq and Ribo-seq. We envision that this review can inspire novel improvements in small RNA sequencing and RNA fragment footprinting in future. This article is categorized under: RNA Evolution and Genomics > Computational Analyses of RNA RNA Processing > Processing of Small RNAs Regulatory RNAs/RNAi/Riboswitches > Biogenesis of Effector Small RNAs.

Identification of five new HLA-C alleles by next-generation sequencing.

Five novel HLA-C alleles detected by next-generation sequencing: HLA-C*02:02:73, -C*03:04:106, -C*06:382, -C*07:1114Q and -C*12:408.

Characterisation of the novel HLA-B*35:593 allele using short and long-read sequencing technologies.

The novel HLA-B*35:593 allele, first described in a potential bone marrow donor from Brazil.

Integrated approach to generate artificial samples with low tumor fraction for somatic variant calling benchmarking.

BACKGROUND: High-throughput sequencing (HTS) has become the gold standard approach for variant analysis in cancer research. However, somatic variants may occur at low fractions due to contamination from normal cells or tumor heterogeneity; this poses a significant challenge for standard HTS analysis pipelines. The problem is exacerbated in scenarios with minimal tumor DNA, such as circulating tumor DNA in plasma. Assessing sensitivity and detection of HTS approaches in such cases is paramount, but time-consuming and expensive: specialized experimental protocols and a sufficient quantity of samples are required for processing and analysis. To overcome these limitations, we propose a new computational approach specifically designed for the generation of artificial datasets suitable for this task, simulating ultra-deep targeted sequencing data with low-fraction variants and demonstrating their effectiveness in benchmarking low-fraction variant calling. RESULTS: Our approach enables the generation of artificial raw reads that mimic real data without relying on pre-existing data by using NEAT, a fine-grained read simulator that generates artificial datasets using models learned from multiple different datasets. Then, it incorporates low-fraction variants to simulate somatic mutations in samples with minimal tumor DNA content. To prove the suitability of the created artificial datasets for low-fraction variant calling benchmarking, we used them as ground truth to evaluate the performance of widely-used variant calling algorithms: they allowed us to define tuned parameter values of major variant callers, considerably improving their detection of very low-fraction variants. CONCLUSIONS: Our findings highlight both the pivotal role of our approach in creating adequate artificial datasets with low tumor fraction, facilitating rapid prototyping and benchmarking of algorithms for such dataset type, as well as the important need of advancing low-fraction variant calling techniques.

ARGNet: using deep neural networks for robust identification and classification of antibiotic resistance genes from sequences.

BACKGROUND: Emergence of antibiotic resistance in bacteria is an important threat to global health. Antibiotic resistance genes (ARGs) are some of the key components to define bacterial resistance and their spread in different environments. Identification of ARGs, particularly from high-throughput sequencing data of the specimens, is the state-of-the-art method for comprehensively monitoring their spread and evolution. Current computational methods to identify ARGs mainly rely on alignment-based sequence similarities with known ARGs. Such approaches are limited by choice of reference databases and may potentially miss novel ARGs. The similarity thresholds are usually simple and could not accommodate variations across different gene families and regions. It is also difficult to scale up when sequence data are increasing. RESULTS: In this study, we developed ARGNet, a deep neural network that incorporates an unsupervised learning autoencoder model to identify ARGs and a multiclass classification convolutional neural network to classify ARGs that do not depend on sequence alignment. This approach enables a more efficient discovery of both known and novel ARGs. ARGNet accepts both amino acid and nucleotide sequences of variable lengths, from partial (30-50 aa; 100-150 nt) sequences to full-length protein or genes, allowing its application in both target sequencing and metagenomic sequencing. Our performance evaluation showed that ARGNet outperformed other deep learning models including DeepARG and HMD-ARG in most of the application scenarios especially quasi-negative test and the analysis of prediction consistency with phylogenetic tree. ARGNet has a reduced inference runtime by up to 57% relative to DeepARG. CONCLUSIONS: ARGNet is flexible, efficient, and accurate at predicting a broad range of ARGs from the sequencing data. ARGNet is freely available at https://github.com/id-bioinfo/ARGNet , with an online service provided at https://ARGNet.hku.hk . Video Abstract.

Application value of metagenomic next-generation sequencing in hematological patients with high-risk febrile neutropenia.

Background: Metagenomic next-generation sequencing (mNGS) is a novel non-invasive and comprehensive technique for etiological diagnosis of infectious diseases. However, its practical significance has been seldom reported in the context of hematological patients with high-risk febrile neutropenia, a unique patient group characterized by neutropenia and compromised immune responses. Methods: This retrospective study evaluated the results of plasma cfDNA sequencing in 164 hematological patients with high-risk febrile neutropenia. We assessed the diagnostic efficacy and clinical impact of mNGS, comparing it with conventional microbiological tests. Results: mNGS identified 68 different pathogens in 111 patients, whereas conventional methods detected only 17 pathogen types in 36 patients. mNGS exhibited a significantly higher positive detection rate than conventional methods (67.7% vs. 22.0%, P < 0.001). This improvement was consistent across bacterial (30.5% vs. 9.1%), fungal (19.5% vs. 4.3%), and viral (37.2% vs. 9.1%) infections (P < 0.001 for all comparisons). The anti-infective treatment strategies were adjusted for 51.2% (84/164) of the patients based on the mNGS results. Conclusions: mNGS of plasma cfDNA offers substantial promise for the early detection of pathogens and the timely optimization of anti-infective therapies in hematological patients with high-risk febrile neutropenia.

Identifying widespread and recurrent variants of genetic parts to improve annotation of engineered DNA sequences.

Engineered plasmids have been workhorses of recombinant DNA technology for nearly half a century. Plasmids are used to clone DNA sequences encoding new genetic parts and to reprogram cells by combining these parts in new ways. Historically, many genetic parts on plasmids were copied and reused without routinely checking their DNA sequences. With the widespread use of high-throughput DNA sequencing technologies, we now know that plasmids often contain variants of common genetic parts that differ slightly from their canonical sequences. Because the exact provenance of a genetic part on a particular plasmid is usually unknown, it is difficult to determine whether these differences arose due to mutations during plasmid construction and propagation or due to intentional editing by researchers. In either case, it is important to understand how the sequence changes alter the properties of the genetic part. We analyzed the sequences of over 50,000 engineered plasmids using depositor metadata and a metric inspired by the natural language processing field. We detected 217 uncatalogued genetic part variants that were especially widespread or were likely the result of convergent evolution or engineering. Several of these uncatalogued variants are known mutants of plasmid origins of replication or antibiotic resistance genes that are missing from current annotation databases. However, most are uncharacterized, and 3/5 of the plasmids we analyzed contained at least one of the uncatalogued variants. Our results include a list of genetic parts to prioritize for refining engineered plasmid annotation pipelines, highlight widespread variants of parts that warrant further investigation to see whether they have altered characteristics, and suggest cases where unintentional evolution of plasmid parts may be affecting the reliability and reproducibility of science.

Epitope binning for multiple antibodies simultaneously using mammalian cell display and DNA sequencing.

Epitope binning, an approach for grouping antibodies based on epitope similarities, is a critical step in antibody drug discovery. However, conventional methods are complex, involving individual antibody production. Here, we established Epitope Binning-seq, an epitope binning platform for simultaneously analyzing multiple antibodies. In this system, epitope similarity between the query antibodies (qAbs) displayed on antigen-expressing cells and a fluorescently labeled reference antibody (rAb) targeting a desired epitope is analyzed by flow cytometry. The qAbs with epitope similar to the rAb can be identified by next-generation sequencing analysis of fluorescence-negative cells. Sensitivity and reliability of this system are confirmed using rAbs, pertuzumab and trastuzumab, which target human epidermal growth factor receptor 2. Epitope Binning-seq enables simultaneous epitope evaluation of 14 qAbs at various abundances in libraries, grouping them into respective epitope bins. This versatile platform is applicable to diverse antibodies and antigens, potentially expediting the identification of clinically useful antibodies.

Sequencing accuracy and systematic errors of nanopore direct RNA sequencing.

BACKGROUND: Direct RNA sequencing (dRNA-seq) on the Oxford Nanopore Technologies (ONT) platforms can produce reads covering up to full-length gene transcripts, while containing decipherable information about RNA base modifications and poly-A tail lengths. Although many published studies have been expanding the potential of dRNA-seq, its sequencing accuracy and error patterns remain understudied. RESULTS: We present the first comprehensive evaluation of sequencing accuracy and characterisation of systematic errors in dRNA-seq data from diverse organisms and synthetic in vitro transcribed RNAs. We found that for sequencing kits SQK-RNA001 and SQK-RNA002, the median read accuracy ranged from 87% to 92% across species, and deletions significantly outnumbered mismatches and insertions. Due to their high abundance in the transcriptome, heteropolymers and short homopolymers were the major contributors to the overall sequencing errors. We also observed systematic biases across all species at the levels of single nucleotides and motifs. In general, cytosine/uracil-rich regions were more likely to be erroneous than guanines and adenines. By examining raw signal data, we identified the underlying signal-level features potentially associated with the error patterns and their dependency on sequence contexts. While read quality scores can be used to approximate error rates at base and read levels, failure to detect DNA adapters may be a source of errors and data loss. By comparing distinct basecallers, we reason that some sequencing errors are attributable to signal insufficiency rather than algorithmic (basecalling) artefacts. Lastly, we generated dRNA-seq data using the latest SQK-RNA004 sequencing kit released at the end of 2023 and found that although the overall read accuracy increased, the systematic errors remain largely identical compared to the previous kits. CONCLUSIONS: As the first systematic investigation of dRNA-seq errors, this study offers a comprehensive overview of reproducible error patterns across diverse datasets, identifies potential signal-level insufficiency, and lays the foundation for error correction methods.

Single-base resolution quantitative genome methylation analysis in the model bacterium Helicobacter pylori by enzymatic methyl sequencing (EM-Seq) reveals influence of strain, growth phase, and methyl homeostasis.

BACKGROUND: Bacterial epigenetics is a rapidly expanding research field. DNA methylation by diverse bacterial methyltransferases (MTases) contributes to genomic integrity and replication, and many recent studies extended MTase function also to global transcript regulation and phenotypic variation. Helicobacter pylori is currently one of those bacterial species which possess the highest number and the most variably expressed set of DNA MTases. Next-generation sequencing technologies can directly detect DNA base methylation. However, they still have limitations in their quantitative and qualitative performance, in particular for cytosine methylation. RESULTS: As a complementing approach, we used enzymatic methyl sequencing (EM-Seq), a technology recently established that has not yet been fully evaluated for bacteria. Thereby, we assessed quantitatively, at single-base resolution, whole genome cytosine methylation for all methylated cytosine motifs in two different H. pylori strains and isogenic MTase mutants. EM-Seq reliably detected both m5C and m4C methylation. We demonstrated that three different active cytosine MTases in H. pylori provide considerably different levels of average genome-wide single-base methylation, in contrast to isogenic mutants which completely lost specific motif methylation. We found that strain identity and changed environmental conditions, such as growth phase and interference with methyl donor homeostasis, significantly influenced quantitative global and local genome-wide methylation in H. pylori at specific motifs. We also identified significantly hyper- or hypo-methylated cytosines, partially linked to overlapping MTase target motifs. Notably, we revealed differentially methylated cytosines in genome-wide coding regions under conditions of methionine depletion, which can be linked to transcript regulation. CONCLUSIONS: This study offers new knowledge on H. pylori global and local genome-wide methylation and establishes EM-Seq for quantitative single-site resolution analyses of bacterial cytosine methylation.

The Third-Generation Sequencing Challenge: Novel Insights for the Omic Sciences.

The understanding of the human genome has been greatly improved by the advent of next-generation sequencing technologies (NGS). Despite the undeniable advantages responsible for their widespread diffusion, these methods have some constraints, mainly related to short read length and the need for PCR amplification. As a consequence, long-read sequencers, called third-generation sequencing (TGS), have been developed, promising to overcome NGS. Starting from the first prototype, TGS has progressively ameliorated its chemistries by improving both read length and base-calling accuracy, as well as simultaneously reducing the costs/base. Based on these premises, TGS is showing its potential in many fields, including the analysis of difficult-to-sequence genomic regions, structural variations detection, RNA expression profiling, DNA methylation study, and metagenomic analyses. Protocol standardization and the development of easy-to-use pipelines for data analysis will enhance TGS use, also opening the way for their routine applications in diagnostic contexts.

Comparison of diagnostic performance among Abbott RealTime HCV Genotyping II, Abbott HCV Genotype plus RUO, and Roche Cobas HCV Genotyping assays for hepatitis C virus genotyping.

Comparison of diagnostic accuracy for commercial hepatitis C virus (HCV) genotyping (Abbott RealTime HCV Genotyping II, Roche Cobas Genotyping) and investigational Abbott HCV Genotype plus RUO assays designed to discriminate genotype (GT)-1a, 1b or 6 in cases of ambiguous GT from the Abbott commercial assay remains limited. 743 HCV-viremic samples were subjected to analysis using Abbott and Roche commercial as well as Abbott HCV Genotype plus RUO assays. Next-generation sequencing (NGS) targeting core region was employed as the reference standard. Diagnostic accuracy was reported as the number of participants (percentages) along with 95% confidence intervals (CIs). Using NGS, 741 samples (99.7%) yielded valid genotyping results. The diagnostic accuracies were 97.6% (95% CI: 96.1%-98.5%) and 95.3% (95% CI: 93.4%-96.6%) using Abbott and Roche commercial assays (p = 0.0174). Abbott commercial assay accurately diagnosed HCV GT-6a and 6w, whereas Roche commercial assay accurately diagnosed HCV GT-6a. Both assays demonstrated low accuracies for HCV GT-6b, 6e, 6g, and 6n. Abbott HCV Genotype plus RUO assay discriminated 13 of the 14 samples (92.9%; 95% CI: 64.2%-99.6%) that yielded ambiguous GT. Both assays were capable of diagnosing mixed HCV infections when the minor genotype comprised >8.4% of the viral load. The diagnostic performance of commercial HCV genotyping assays is commendable. Abbott assay demonstrated superior performance compared to Roche assay in diagnosing HCV GT-6. Abbott HCV Genotype plus RUO assay aids in discriminating ambiguous GT. Both commercial assays are proficient in diagnosing mixed HCV infections at a cut-off viral load of 8.4% in minor genotype.

Haplotype determination of the Bombyx mori nucleopolyhedrovirus by Nanopore sequencing and linkage of single nucleotide variants.

Naturally occurring isolates of baculoviruses, such as the Bombyx mori nucleopolyhedrovirus (BmNPV), usually consist of numerous genetically different haplotypes. Deciphering the different haplotypes of such isolates is hampered by the large size of the dsDNA genome, as well as the short read length of next generation sequencing (NGS) techniques that are widely applied for baculovirus isolate characterization. In this study, we addressed this challenge by combining the accuracy of NGS to determine single nucleotide variants (SNVs) as genetic markers with the long read length of Nanopore sequencing technique. This hybrid approach allowed the comprehensive analysis of genetically homogeneous and heterogeneous isolates of BmNPV. Specifically, this allowed the identification of two putative major haplotypes in the heterogeneous isolate BmNPV-Ja by SNV position linkage. SNV positions, which were determined based on NGS data, were linked by the long Nanopore reads in a Position Weight Matrix. Using a modified Expectation-Maximization algorithm, the Nanopore reads were assigned according to the occurrence of variable SNV positions by machine learning. The cohorts of reads were de novo assembled, which led to the identification of BmNPV haplotypes. The method demonstrated the strength of the combined approach of short- and long-read sequencing techniques to decipher the genetic diversity of baculovirus isolates.

Identification of novel and known genetic variants associated with hereditary hearing loss in iranian families using whole exome sequencing.

BACKGROUND: Hearing loss (HL) is a common sensory impairment worldwide, with genetic and environmental factors contributing to its occurrence. Next Generation Sequencing (NGS) plays a crucial role in identifying the genetic factors involved in this heterogeneous disorder. METHODS AND RESULTS: In this study, a total of 9 unrelated Iranian families, each having at least one affected individual who tested negative for mutations in GJB2, underwent screening using whole exome sequencing (WES). The pathogenicity and novelty of the identified variant was checked using various databases. Co-segregation study was also performed to confirm the presence of the candidate variants in parents. Plus, The pathogenicity of the detected variant was assessed through in silico analysis using a number of mutation prediction software tools. Among the 9 investigated families, hearing loss-causing genes were identified in 6 families. the mutations were observed in USH2A, CLRN1, BSND, SLC26A4, and MITF, with two of the identified mutations being novel. CONCLUSION: Discovering additional variants and broadening the range of mutations associated with hearing impairment has the potential to enhance the diagnostic effectiveness of molecular testing in patient screening, and can also lead to improved counseling aimed at reducing the risk of affected offspring for high-risk couples.

Application of metagenomic next-generation sequencing in optimizing the diagnosis of ascitic infection in patients with liver cirrhosis.

BACKGROUND: Metagenomic next-generation sequencing (mNGS) is an emerging technique for the clinical diagnosis of infectious disease that has rarely been used for the diagnosis of ascites infection in patients with cirrhosis. This study compared mNGS detection with conventional culture methods for the on etiological diagnosis of cirrhotic ascites and evaluated the clinical effect of mNGS. METHODS: A total of 109 patients with ascites due to cirrhosis were included in the study. We compared mNGS with conventional culture detection by analyzing the diagnostic results, pathogen species and clinical effects. The influence of mNGS on the diagnosis and management of ascites infection in patients with cirrhosis was also evaluated. RESULTS: Ascites cases were classified into three types: spontaneous bacterial peritonitis (SBP) (16/109, 14.7%), bacterascites (21/109, 19.3%) and sterile ascites (72/109, 66.1%). In addition, 109 patients were assigned to the ascites mNGS-positive group (80/109, 73.4%) or ascites mNGS-negative group (29/109, 26.6%). The percentage of positive mNGS results was significantly greater than that of traditional methods (73.4% vs. 28.4%, P < 0.001). mNGS detected 43 strains of bacteria, 9 strains of fungi and 8 strains of viruses. Fourteen bacterial strains and 3 fungal strains were detected via culture methods. Mycobacteria, viruses, and pneumocystis were detected only by the mNGS method. The mNGS assay produced a greater polymicrobial infection rate than the culture method (55% vs. 16%). Considering the polymorphonuclear neutrophil (PMN) counts, the overall percentage of pathogens detected by the two methods was comparable, with 87.5% (14/16) in the PMN ≥ 250/mm3 group and 72.0% (67/93) in the PMN < 250/mm3 group (P > 0.05). Based on the ascites PMN counts combined with the mNGS assay, 72 patients (66.1%) were diagnosed with ascitic fluid infection (AFI) (including SBP and bacterascites), whereas based on the ascites PMN counts combined with the culture assay, 37 patients (33.9%) were diagnosed with AFI (P < 0.05). In 60 (55.0%) patients, the mNGS assay produced positive clinical effects; 40 (85.7%) patients had their treatment regimen adjusted, and 48 patients were improved. The coincidence rate of the mNGS results and clinical findings was 75.0% (60/80). CONCLUSIONS: Compared with conventional culture methods, mNGS can improve the detection rate of ascites pathogens, including bacteria, viruses, and fungi, and has significant advantages in the diagnosis of rare pathogens and pathogens that are difficult to culture; moreover, mNGS may be an effective method for improving the diagnosis of ascites infection in patients with cirrhosis, guiding early antibiotic therapy, and for reducing complications related to abdominal infection. In addition, explaining mNGS results will be challenging, especially for guiding the treatment of infectious diseases.

The diagnostic value of metagenomics next-generation sequencing in HIV-infected patients with suspected pulmonary infections.

Background: Traditional microbiological detection methods used to detect pulmonary infections in people living with HIV (PLHIV) are usually time-consuming and have low sensitivity, leading to delayed treatment. We aimed to evaluate the diagnostic value of metagenomics next-generation sequencing (mNGS) for microbial diagnosis of suspected pulmonary infections in PLHIV. Methods: We retrospectively analyzed PLHIV who were hospitalized due to suspected pulmonary infections at the sixth people hospital of Zhengzhou from November 1, 2021 to June 30, 2022. Bronchoalveolar lavage fluid (BALF) samples of PLHIV were collected and subjected to routine microbiological examination and mNGS detection. The diagnostic performance of the two methods was compared to evaluate the diagnostic value of mNGS for unknown pathogens. Results: This study included a total of 36 PLHIV with suspected pulmonary infections, of which 31 were male. The reporting period of mNGS is significantly shorter than that of CMTs. The mNGS positive rate of BALF samples in PLHIV was 83.33%, which was significantly higher than that of smear and culture (44.4%, P<0.001). In addition, 11 patients showed consistent results between the two methods. Futhermore, mNGS showed excellent performance in identifying multi-infections in PLHIV, and 27 pathogens were detected in the BALF of 30 PLHIV by mNGS, among which 15 PLHIV were found to have multiple microbial infections (at least 3 pathogens). Pneumocystis jirovecii, human herpesvirus type 5, and human herpesvirus type 4 were the most common pathogen types. Conclusions: For PLHIV with suspected pulmonary infections, mNGS is capable of rapidly and accurately identifying the pathogen causing the pulmonary infection, which contributes to implement timely and accurate anti-infective treatment.