Next-generation Sequencing Research Articles

Characterization of N6-methyladenosine long non-coding RNAs in sporadic congenital cataract and age-related cataract

AIM: To characterize the N6-methyladenosine (m6A) modification patterns in long non-coding RNAs (lncRNAs) in sporadic congenital cataract (CC) and age-related cataract (ARC). METHODS: Anterior capsule of the lens were collected from patients with CC and ARC. Methylated RNA immunoprecipitation with next-generation sequencing and RNA sequencing were performed to identify m6A-tagged lncRNAs and lncRNAs expression. Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses and Gene Ontology annotation were used to predict potential functions of the m6A-lncRNAs. RESULTS: Large amount of m6A peaks within lncRNA were identified for both CC and ARC, while the level was much higher in ARC (49 870 peaks) than that in CC (18 688 peaks), yet those difference between ARC in younger age group (ARC-1) and ARC in elder age group (ARC-2) was quite slight. A total of 1305 hypermethylated and 1178 hypomethylated lncRNAs, as well as 182 differential expressed lncRNAs were exhibited in ARC compared with CC. On the other hand, 5893 hypermethylated and 5213 hypomethylated lncRNAs, as well as 155 significantly altered lncRNA were identified in ARC-2 compared with ARC-1. Altered lncRNAs in ARC were mainly associated with the organization and biogenesis of intracellular organelles, as well as nucleotide excision repair. CONCLUSION: Our results for the first time present an overview of the m6A methylomes of lncRNA in CC and ARC, providing a solid basis and uncovering a new insight to reveal the potential pathogenic mechanism of CC and ARC.

Genetic species concept as applied to multilocus nuclear data

Using the example of multiple species groups and species complexes, it is empirically shown that the resolving power of a set of 10–20 nuclear loci is insufficient for the study of their genetic differentiation. For the adequate analysis of phylogenetic relationships (including reticulation events) and assessment of divergence levels within such groups of closely related species, it is necessary to multiply the number of nuclear loci and transit to high-throughput next-generation deep sequencing. However, the question of the genomic coverage required for the purposes of such study remains open. In other words, exactly how many genes in a set are needed to measure the genetic distance resolving the relationships between branches on the phylogenetic tree reconstruction of a complex of closely related species? We chose protein-coding sequences as a standard set of markers. Distances for 160–180 genes with a combined length of 270 000–300 000 bp were used to estimate the divergence levels of closely related mammalian species. In most cases, the interspecific distances are within the 0.15–0.75% range (median of 0.33%). The range of distances between semi-species is 0.12–0.28% (median of 0.14%). Intraspecific distances are always lower than 0.11%. Rodents show higher values of interspecific distances, 0.25–2.3% (median of 0.72%); distances between half-species range from 0.1 to 0.35%. To determine the number of nuclear loci and their combined length sufficient for the calculation of a genetic distance, we use simulations based on a model that included the following parameters: the average rate of gene evolution, its dispersion, and the level of polymorphism in the modern and ancestral populations. We performed a preliminary analysis of the distribution of loci evolution rates among mammalian taxa based on the data on ~50 thousand nuclear markers. It is shown that a relative error of 10–15%, comparable to the same value for mitochondrial distances between close species based on individual genes (approximately 1000 bp in length), is achieved using approximately 100 loci of 300 bp in length. Based on these data, we propose the following working hypothesis: the threshold of interspecific/intraspecific genetic distance calculated on the basis of the exons most frequently used in mammalian molecular phylogenetics is approximately 0.15%. This hypothesis assumes a species rank for the forms in statu nascendi. It should be noted that not all “good” species have significant genetic distances, since in some cases reproductive barriers form faster than substitutions accumulate in the genome.

Combining interferon-γ release assays and metagenomic next-generation sequencing for diagnosis of pulmonary tuberculosis: a retrospective study

Combining interferon-γ release assays and metagenomic next-generation sequencing for diagnosis of pulmonary tuberculosis: a retrospective study

Abstract B016: Utilizing gene expression profiles (GEP) to assess tumor microenvironment (TME) and response to immunotherapy

Abstract Background: Despite the success of anti-PD-1/PD-L1 immunotherapies, outcomes for lung cancer patients remain suboptimal. There is a critical need to incorporate multi-omics data focused on the tumor microenvironment (TME) to enhance patient selection and treatment individualization. This study aimed to identify predictive and prognostic biomarkers of immunotherapy response by characterizing transcriptional profiles of lung adenocarcinoma patients who underwent genomic profiling at diagnosis. Methods: RNA sequencing data were obtained from 68 lung adenocarcinoma patients who underwent next-generation sequencing with CARIS at our institution. We analyzed gene expression profiles (GEP) comprising 18 inflammatory genes associated with antigen presentation, chemokine expression, cytolytic activity, and adaptive immune resistance, identified as potential biomarkers for immune checkpoint inhibitor (ICI) response (Cristescu et al., 2018). The genes included were CCL5, CD27, CD274 (PD-L1), CD276 (B7-H3), CD8A, CMKLR1, CXCL9, CXCR6, HLA-DQA1, HLA-DRB1, HLA-E, IDO1, LAG3, NKG7, PDCD1LG2 (PD-L2), PSMB10, STAT1, and TIGIT. GEP scores were calculated, and hierarchical clustering identified tumor subsets with similar GEPs. Gene set variation analysis was conducted to assess enrichment of cell-cell interaction activities of specific ligand-receptor pairs of immune checkpoint genes, partially overlapping with the 18 GEP genes. Results: Hierarchical clustering identified four distinct GEP clusters: "T cell-inflamed GEP," "T cell-non-inflamed GEP high," "T cell-non-inflamed GEP medium," and "T cell-non-inflamed low GEP," with average scores of 0.18 (N=9, 13%), 0.11 (N=29, 43%), 0.08 (N=19, 28%), and 0.04 (N=11, 16%), respectively. The gene scores among these clusters showed significant differences (P = 3.3e-09). Additionally, analysis of specific ligand-receptor pairs of immune checkpoint genes (PD1/PD-L1, PD-L2; CTLA4/CD28, CD80, CD86; ICOS/ICOSLG; TIM3/GAL9; SIRP1/CD47) showed consistent positive enrichment in the “T cell-inflamed” cluster, with no or negative enrichment in the “T cell-non-inflamed” clusters. This suggests active immune checkpoint interactions in clusters with high GEP scores. Conclusion: We identified four different clusters among tissues from patients with NSCLC based on GEP scoring highlighting differences in immune activation and TME makeup, which may play a role in predicting response to immunotherapies. Our results suggest that GEP may provide information on identifying optimal immunotherapeutic approaches based on TME. Our findings underscore the importance of using biomarker-guided strategies to improve patient selection for precision immunotherapy approaches in lung cancer. Citation Format: Changde Cheng, Doug Welsch, Kayla F. Goliwas, Jessy Deshane, Sameer Deshmukh, Sanad Ahlushki, Yanis Boumber, Darshan Shimoga Chandrashekar, Alexander C. Mackinnon, Aakash Desai. Utilizing gene expression profiles (GEP) to assess tumor microenvironment (TME) and response to immunotherapy [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Tumor-body Interactions: The Roles of Micro- and Macroenvironment in Cancer; 2024 Nov 17-20; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(22_Suppl):Abstract nr B016.

Role of gut microbiome in developing necrotizing enterocolitis.

Necrotizing enterocolitis (NEC) is one of the most devastating intestinal diseases observed in preterm in the first days of life. Researchers have recently focused on potential predictive biomarkers for early and concomitant diagnoses. Thus, we inquired about the linkage of intestinal dysbiosis, one of the most important factors in NEC development to the gut microbiota. In this study, the systematic differences in the bacterial composition between neonates affected by NEC and healthy newborns were highlighted by metagenomic analysis. The next-generation sequencing of the V3-V4 variable region of the 16S rRNA gene and gene-specific qPCR analyzed the untargeted gut microbiota. Total bacteria, total and fecal coliform loads in stool samples with NEC were higher than control. OTU-level relative abundances of NEC infant was characterized by Firmicutes and Bacteroidetes at phylum levels. At the genus level, NEC stool was identified by the lack of Klebsiella and the presence of Roseburia, Blautia, and Parasutterella. Finally, Clostridium fessum was the predominant species of Clostridium genus in disease and healthy specimens at the species level, whereas Clostridium jeddahitimonense was at NEC diagnosis. Despite a strong relationship between pathophysiology and characterization of gut microbiota at a clinical diagnosis of NEC, our results emphasize the broad difficulty in identifying potential biomarkers.

Testing the informativeness of Y-STR and mitochondrial DNA control region markers in an attempt to predict ancestry of World War II victims from Slovenian mass grave.

Identification of human remains is a challenge in forensic genetics without relatives or personal items available. In Slovenia, a Konfin II mass grave from the Second World War (WWII) was found, containing skeletal remains of 65 victims. The archival documents detailing victims' information describe 45 persons of which 33 could be considered Germanic and 12 Slavic. This study aims to check for concordance between the victim list and actual victims found by using uniparental markers to differentiate between Slavic and non-Slavic origin by attempting to infer ancestry by analyzing the control region (CR) of mitochondrial DNA (mtDNA) and Y-chromosomal STRs. Diaphyses of femurs were used as a DNA source. Next Generation Sequencing (NGS) technology was used for mtDNA- namely HID Ion Chef™ Instrument, Precision ID mtDNA Control Region Panel, and Ion GeneStudio™ S5 System. For the Y-chromosome, PowerPlex® Y23 System (Promega) kit and SeqStudio™ for human identification (HID) were used. European DNA Profiling mtDNA Population Database (EMPOP) and Y-Chromosome STR Haplotype Reference Database (YHRD) were searched for haplotype matches. Closest haplogroups were predicted using EMPOP, Y-DNA Haplogroup Predictor- NevGen, and Whit Athey's Haplogroup Predictor. Despite mitotypes being more diverse than Y-haplotypes, the Y-haplotypes had more database matches and more unequivocal differentiation between populations. 16 victims could be considered Slavic, 15 non-Slavic, and the remaining 34 had a rather scarce informativeness- either unclear or not providing any match. To address ancestry inference more comprehensively, analysis of autosomal ancestry informative markers as well as expansion on haploid markers will be conducted in future research.

A series of genetically confirmed congenital lipodystrophy and diabetes in adult southern Indian patients.

In this study, we analysed the mutation spectrum in subjects with suspected lipodystrophy using a targeted Next-generation sequencing (NGS) approach. Subjects with suspected lipodystrophy were for screened six genes (AGPAT2, BSCL2, LMNA, PPARG, ZMPSTE24, INSR) and the variants identified were confirmed through Sanger sequencing. The clinical and biochemical parameters were compared among the mutation positive and negative subjects. We identified eight individuals with pathogenic or likely pathogenic mutations, including both homozygous and heterozygous variants. Homozygous variants included AGPAT2(NM_006412.4):c.493-2A>G, AGPAT2(NM_006412.4):c.254_258dup, and BSCL2(NM_001122955.4):c.570del, while heterozygous variants encompassed LMNA(NM_170707.4):c.1444C>T, LMNA(NM_170707.4):c.1456A>G, LMNA(NM_170707.4):c.1445G>A, and PPARG(NM_015869.5):c.949T>C mutations. In this cohort, three subjects were diagnosed with congenital generalized lipodystrophy, while the remaining five had familial partial lipodystrophy. Majority (7/8) of the patients with lipodystrophy had hepatic involvement. Notably, more than half of the subjects (5/8) achieved optimal glycemic control through insulin sensitizers (PPARγ agonist and Metformin). Interestingly, even with a limited gene panel test, mutation-positive individuals exhibited a higher prevalence of typical clinical features and biochemical characteristics associated with lipodystrophy compared to their mutation-negative counterparts. In subjects with lipodystrophy, targeted NGS based screening may establish a genetic diagnosis and aid in family screening and genetic counselling. Knowing the clinical and biochemical features typical to lipodystrophy may help in diagnosis especially in resource limited setting.

Can Talaromyces marneffei Infection Cause Acute Liver Failure? A Case Report

Introduction: Talaromyces marneffei is a pathogen that causes talaromycosis, a systemic fungal infection. Cases in which hepatic failure is the primary clinical presentation are exceedingly rare. Case Presentation: This report details the case of a 49-year-old male with no prior liver disease, presenting to the hospital with persistent symptoms, including a fever lasting over ten days, abdominal distension for five days, and jaundice for three days. The patient’s history included immune thrombocytopenia and prolonged glucocorticoid therapy. Physical examination revealed yellowing of the skin and sclera, abdominal distension, firmness of the abdominal wall, absence of abdominal tenderness, positive shifting dullness, and pitting edema in the lumbosacral region and bilateral lower extremities. An HIV antibody test was negative. The patient developed hepatic failure and received artificial liver support along with routine therapy. Despite these interventions, the patient was automatically discharged without improvement and subsequently passed away. Post-discharge, cultures from pleural and abdominal effusions identified Talaromyces marneffei. Conclusions: Talaromyces marneffei infection should be considered in the differential diagnosis of immunocompromised patients, particularly those with no history of liver disease but with long-term glucocorticoid or immunosuppressant use who present with acute liver failure. Early and aggressive investigation for the causative pathogen is essential to minimize diagnostic and treatment delays. Given the prolonged incubation period of Talaromyces marneffei, metagenomic next-generation sequencing may offer a more rapid approach for etiological diagnosis.

Detection of genetic mutations in 855 cases of papillary thyroid carcinoma by next generation sequencing and its clinicopathological features.

To investigate the genetic mutations in patients with papillary thyroid carcinoma (PTC) and their clinicopathological features by next generation sequencing (NGS). NGS technology was used to detect genetic mutations in PTC patients, and clinicopathological features were collected. ①Among 855 PTC patients, 810 patients had genetic mutations, and 45 patients had no genetic mutation. ②BRAF mutation was associated with tumor diameter (P < 0.001) and histological subtypes (P = 0.002). The abundance of V600E mutation was associated with gender (P = 0.004), tumor diameter (P < 0.001), bilateral presentation (P = 0.001), extrathyroidal extension (P < 0.001), lymphatic metastasis (P < 0.001), histological subtypes (P = 0.002) and TNM staging (P = 0.000); The different mutation abundance of V600E was associated with tumor diameter (P < 0.001), multifocal presentation (P = 0.047), bilateral presentation (P = 0.001), extrathyroidal extension (P = 0.001), lymphatic metastasis (P < 0.001), histological subtypes (P = 0.022) and TNM staging (P = 0.000). ③RET fusion was associated with tumor diameter (P < 0.001) and lymphatic metastasis (P = 0.005). ④TERT mutation was associated with gender (P = 0.043), tumor diameter (P < 0.001), extrathyroidal extension (P = 0.028) and TNM staging (P = 0.017). ⑤RAS mutation was associated with histological subtypes (P < 0.001). ⑥NTRK and PIK3CA mutations were not associated with clinicopathological features. NGS technology can comprehensively analyze the genetic mutations in PTC patients, which provides important prompts for the occurrence, development, diagnosis and treatment of PTC. In addition, BRAF V600E mutation, RET fusion and TERT mutation are associated with a number of high-risk clinicopathological features. Detection of genetic mutations in PTC patients by NGS is of great significance.

Next step of molecular pathology: next-generation sequencing in cytology

The evolving landscape of precision oncology underscores the pivotal shift from morphological diagnosis to treatment decisions driven by molecular profiling. Recent guidelines from the European Society for Medical Oncology recomend the use of next-generation sequencing (NGS) across a broader range of cancers, reflecting its superior efficiency and clinical value. NGS not only updates oncology testing by offering quicker, sample-friendly, and sensitive analysis but also reduces the need for multiple individual tests. Cytology samples, often obtained through less invasive methods, can yield high-quality genetic material suitable for molecular analysis. This article focuses on optimizing the use of cytology samples in NGS, and outlines their potential benefits in identifying actionable molecular alterations for targeted therapies across various solid tumors. It also addresses the need for validation studies and the strategies to incorporate or combine different types of samples into routine clinical practice. Integrating cytological and liquid biopsies into routine clinical practice, alongside conventional tissue biopsies, offers a comprehensive approach to tumor genotyping, early disease detection, and monitoring of therapeutic responses across various solid tumor types. For comprehensive biomarker characterization, all patient specimens, although limited, is always valuable.

Germline Variant Spectrum in Southern Italian High-Risk Hereditary Breast Cancer Patients: Insights from Multi-Gene Panel Testing

Hereditary breast cancer accounts for 5–10% of all cases, with pathogenic variants in BRCA1/2 and other susceptibility genes playing a crucial role. This study elucidates the prevalence and spectrum of germline variants in 13 cancer predisposition genes among high—risk hereditary breast cancer patients from Southern Italy. We employed next-generation sequencing (NGS) to analyze 254 individuals selected through genetic counseling. Pathogenic or likely pathogenic variants were identified in 13% (34/254) of patients, with 54% of these variants occurring in non-BRCA1/2 genes. Notably, we observed a recurrent BRCA1 c.4964_4982del founder mutation, underscoring the importance of population-specific genetic screening. The spectrum of variants extended beyond BRCA1/2 to include PALB2, ATM, TP53, CHEK2, and RAD51C, highlighting the genetic heterogeneity of breast cancer susceptibility. Variants of uncertain significance were detected in 20% of patients, emphasizing the ongoing challenge of variant interpretation in the era of multi-gene panel testing. These findings not only enhance our understanding of the genetic landscape of breast cancer in Southern Italy but also provide a foundation for developing more targeted, population-specific approaches to genetic testing and counseling, ultimately contributing to the advancement of precision medicine in oncology.

Transcriptional Responses of Lacticaseibacillus rhamnosus to TNFα, IL-6, IL-8, and IL-10 Cytokines

The interaction between gut microbiota and the host immune system is a complex and understudied field, with cytokines like TNFα, IL-6, IL-8, and IL-10 playing pivotal roles. Commensal bacteria, including lactobacilli, respond to these cytokines through adaptive mechanisms that support their survival and function within the gut. While the influence of cytokines on pathogenic bacteria is well documented, their impact on commensal bacteria, particularly lactobacilli, remains underexplored. This study investigates the transcriptional responses of Lacticaseibacillus rhamnosus strains K32 and R19-3 to various cytokines using next-generation RNA sequencing (RNA-seq). Our findings reveal that cytokines, especially IL-8 and IL-10, significantly alter the L. rhamnosus transcriptome, affecting genes involved in carbohydrate metabolism, stress response, and transcriptional regulation. Notably, IL-8 and IL-10 induce a significant downregulation of genes related to the phosphotransferase system, suggesting a reduction in metabolic activity in response to inflammatory signals. This study unveils a previously unexplored aspect of L. rhamnosus adaptation, highlighting its intricate response to cytokine signals. By modulating gene expression, L. rhamnosus may mitigate the adverse effects of inflammation and promote gut health. These insights could inform the development of targeted probiotic therapies for inflammatory bowel disease (IBD) and other conditions with altered cytokine levels. Our results suggest that co-evolution between a host and gut microbiota enables bacteria to respond to specific cytokines through gene expression changes, revealing a unique and underexplored facet of the interaction between commensal bacteria and the host organism.

DMD mutations in pediatric patients with phenotypes of Duchenne/Becker muscular dystrophy

Abstract Duchenne muscular dystrophy (DMD) and Becker muscular dystrophy (BMD) are common X-inherited neuromuscular diseases. The genetic diagnosis has been used as the diagnostic choice for DMD/BMD. The study subjects consisted of 37 patients from Southwest China. Peripheral blood was collected for the extraction of genomic DNA. DMD mutation was sequenced using the next-generation sequencing approach. The detected mutation was validated using the multiplex ligation-dependent probe amplification or Sanger sequencing methods. Variation annotation and pathogenicity prediction were performed using the online databases. Pathogenic mutations were identified 3 splicing site, 7 single nucleotide, 1 indel, 23 deletion, and 3 duplication mutations. Novel DMD variants were discovered, including two novel splicing variations (c.1890 + 1G&gt;T; c.1923 + 1G&gt;A), one missense mutation (c.1946G&gt;T), one nonsense mutation (c.7441G&gt;T), one indel mutation (INDEL EX20), and one duplication mutation (DUP EX75-78). The current study provides mutation information of DMD for the genetic diagnosis of DMD/BMD.

Technical challenges of intracellular flow cytometry-based assays as a functional complement to diagnosis of signaling defects of inborn errors of immunity: PI3K pathway as a case of study

BackgroundThe use of next-generation sequencing in inborn errors of immunity (IEI) has considerably increased the identification of novel gene variants, many of which are identified in patients without the described clinical phenotype or with variants of uncertain pathogenic significance in previously described genes. Properly designed functional and cellular assays, many necessarily accomplished by research-based laboratories, reveal the pathogenic consequences of the gene variants and contribute to diagnosis. Activated PI3Kδ syndrome (APDS) is a rare disease that can be divided into APDS1, caused by gain of function (GOF) mutations in PIK3CD gene, and APDS2, with loss of function (LOF) variants in the PIK3R1 gene. Both entities present hyperactivation of the PI3K pathway, which can be analyzed through Akt and S6 phosphorylation status.MethodsOur objective was to perform an accurate, robust, and reproducible functional assay to analyze the phosphorylation status of proteins in the PI3K-Akt-S6 pathway by flow cytometry, to contribute to diagnosis, to monitor treatments, and to establish intra-assay standardization.ResultsWe illustrate the robustness and reproducibility of our experimental procedure in patients with APDS who had high Akt and/or S6 phosphorylation levels at baseline, and after anti-IgM stimulation in B cells. We show the relevance of an appropriate cohort of samples from healthy donors, processed within the same conditions as the suspected samples, in particular the time frame for sample processing once blood is collected.DiscussionWe highlight the importance of B cell stimulation through B cell receptor signaling, which is highly recommended, especially for samples that would be processed more than 24 hours after blood extraction. Also, having a defined experimental procedure is important, including the cytometer setup, which allows cytometer reproducibility for a period of time, enabling the comparison of a sample at different times.

Enriching the future of public health microbiology with hybridization bait capture.

SUMMARYPublic health microbiology focuses on microorganisms and infectious agents that impact human health. For years, this field has relied on culture or molecular methods to investigate complex samples of public health importance. However, with the increase in accuracy and decrease in sequencing cost over the last decade, there has been a transition to the use of next-generation sequencing in public health microbiology. Nevertheless, many available sequencing methods (e.g., shotgun metagenomics and amplicon sequencing) do not work well in complex sample types, require deep sequencing, or have inherent biases associated with them. Hybridization bait capture, also known as target enrichment, brings in solutions for such limitations. It is an increasingly popular technique to simultaneously characterize many thousands of genetic elements while reducing the amount of sequencing needed (thereby reducing the sequencing costs). Here, we summarize the concept of hybridization bait capture for public health, reviewing a total of 35 bait sets designed in six key topic areas for public health microbiology [i.e., antimicrobial resistance (AMR), bacteria, fungi, parasites, vectors, and viruses], and compare hybridization bait capture to previously relied upon methods. Furthermore, we provide an in-depth comparison of the three most popular bait sets designed for AMR by evaluating each of them against three major AMR databases: Comprehensive Antibiotic Resistance Database, Microbial Ecology Group Antimicrobial Resistance Database, and Pathogenicity Island Database. Thus, this article provides a review of hybridization bait capture for public health microbiologists.

Application of metagenomic next-generation sequencing in the diagnosis of infectious diseases

Metagenomic next-generation sequencing (mNGS) is a transformative approach in the diagnosis of infectious diseases, utilizing unbiased high-throughput sequencing to directly detect and characterize microbial genomes from clinical samples. This review comprehensively outlines the fundamental principles, sequencing workflow, and platforms utilized in mNGS technology. The methodological backbone involves shotgun sequencing of total nucleic acids extracted from diverse sample types, enabling simultaneous detection of bacteria, viruses, fungi, and parasites without prior knowledge of the infectious agent. Key advantages of mNGS include its capability to identify rare, novel, or unculturable pathogens, providing a more comprehensive view of microbial communities compared to traditional culture-based methods. Despite these strengths, challenges such as data analysis complexity, high cost, and the need for optimized sample preparation protocols remain significant hurdles. The application of mNGS across various systemic infections highlights its clinical utility. Case studies discussed in this review illustrate its efficacy in diagnosing respiratory tract infections, bloodstream infections, central nervous system infections, gastrointestinal infections, and others. By rapidly identifying pathogens and their genomic characteristics, mNGS facilitates timely and targeted therapeutic interventions, thereby improving patient outcomes and infection control measures. Looking ahead, the future of mNGS in infectious disease diagnostics appears promising. Advances in bioinformatics tools and sequencing technologies are anticipated to streamline data analysis, enhance sensitivity and specificity, and reduce turnaround times. Integration with clinical decision support systems promises to further optimize mNGS utilization in routine clinical practice. In conclusion, mNGS represents a paradigm shift in the field of infectious disease diagnostics, offering unparalleled insights into microbial diversity and pathogenesis. While challenges persist, ongoing technological advancements hold immense potential to consolidate mNGS as a pivotal tool in the armamentarium of modern medicine, empowering clinicians with precise, rapid, and comprehensive pathogen detection capabilities.

A review of multiple diagnostic approaches in the undiagnosed diseases network to identify inherited metabolic diseases.

The number of known inherited metabolic diseases (IMDs) has been expanding, and the rate of diagnosis is improving with the development of innovative approaches including next generation sequencing (NGS). However, a substantial proportion of IMDs remain undetected by traditional diagnostic approaches. We aim to highlight the spectrum of IMDs diagnosed by the Undiagnosed Diseases Network (UDN) and to learn from the UDN diagnostic processes that were able to detect IMDs. We conducted a retrospective analysis of 757 UDN participants diagnosed from 2015 until 2023 using the cohort database, which were divided into a cohort with IMDs (n = 194; 27%) and a cohort whose phenotypes were not explained by an IMD (n = 563; 73%), based on the International Classification of Inherited Metabolic Disorders (ICIMD). Then, we divided the causes of the metabolic 194 diagnoses into seven groups that included all the ICIMD categories. We inspected which clinical and laboratory approaches contributed to a final UDN diagnosis. We also present a UDN case example from each group to highlight the diagnostic yields that resulted from combining newer diagnostic approaches in the UDN and illustrate potential pitfalls of current NGS methods. These 194 cases of IMDs included examples from 21/25 (84%) of the ICIMD categories. Of the UDN subjects 164/194 (85%) were diagnosed with IMDs through NGS. The spectrum of IMDs detected in the UDN cohort is large and growing and appropriate use of newer multiple diagnostic approaches should further increase diagnosis of IMDs that are presently missed by the traditional laboratory screening methods.

Unveiling bat-borne viruses: a comprehensive classification and analysis of virome evolution.

Bats (Order Chiroptera) are an important reservoir of emerging zoonotic microbes, including viruses of public health concern such as henipaviruses, lyssaviruses, and SARS-related coronaviruses. Despite the continued discovery of new viruses in bat populations, a significant proportion of these viral agents remain uncharacterized, highlighting the imperative for additional research aimed at elucidating their evolutionary relationship and taxonomic classification. In order to delve deeper into the viral reservoir hosted by bats, the present study employed Next Generation Sequencing (NGS) technology to analyze 13,105 swab samples obtained from various locations in China. Analysis of 378 sample pools revealed the presence of 846 vertebrate-associated viruses. Subsequent thorough examination, adhering to the International Committee on Taxonomy of Viruses (ICTV) criteria for virus classification, identified a total of 120 putative viral species with the potential to emerge as novel viruses, comprising a total of 294 viral strains. Phylogenetic analysis of conserved genomic regions indicated the novel virus exhibited a diverse array of viral lineages and branches, some of which displayed close genetic relationships to known human and livestock pathogens, such as poxviruses and pestiviruses. This study investigates the breadth of DNA and RNA viruses harbored by bats, delineating several novel evolutionary lineages and offering significant contributions to virus taxonomy. Furthermore, the identification of hitherto unknown viruses with relevance to human and livestock health underscores the importance of this study in encouraging infectious disease monitoring and management efforts in both public health and veterinary contexts. Video Abstract.

Sclerosing mucoepidermoid carcinoma of salivary glands.

Sclerosing mucoepidermoid carcinoma (SMEC) of the salivary glands is a rare variant of low-grade mucoepidermoid carcinoma with scanty cellular atypia characterized by marked fibrosis/sclerosis and a rich inflammatory infiltrate. Herein, we report 25 unpublished cases of SMEC, two of them with prominent eosinophilia (2/25; 8%) and three with abundant IgG4-positive plasma cells (3/25; 12%). In our series of salivary SMEC, molecular analysis using fluorescence in situ hybridization (FISH) and/or next-generation sequencing (NGS) provided evidence of MAML2 gene rearrangement in 18 cases of the 21 analyzable cases tested (86%), while this gene locus was intact in 3 cases (14%). This study focuses on the diagnostic criteria of salivary SMEC given its challenge of abundant collagenous stroma, minimal residual neoplastic areas, and inconspicuous mucous cells. Follow-up data of our cases indicate that salivary SMECs have favorable outcomes. Molecular analysis for MAML2 gene rearrangement suggests that SMECs of salivary glands represent a rare variant of conventional low-grade MECs of salivary glands. In contrast, SMECs of the thyroid gland are genetically distinct from salivary-type thyroid MECs.

Precision oncology platforms: practical strategies for genomic database utilization in cancer treatment.

In recent years, the expansion of molecularly targeted cancer therapies has significantly advanced precision oncology. Parallel developments in next-generation sequencing (NGS) technologies have also improved precision oncology applications, making genomic analysis of tumors more affordable and accessible. Targeted NGS panels now enable the rapid identification of diverse actionable mutations, requiring clinicians to efficiently assess the predictive value of cancer biomarkers for specific treatments. The urgency for timely and accurate decision-making in oncology emphasizes the importance of reliable precision oncology software. Online clinical decision-making tools and associated cancer databases have been designed by consolidating genomic data into standardized, accessible formats. These new platforms are highly integrated and crucial for identifying actionable somatic genomic biomarkers essential for tumor survival, determining corresponding drug targets, and selecting appropriate treatments based on the mutational profile of each patient's tumor. To help oncologists and translational cancer researchers unfamiliar with these tools, we review the utility, accuracy, and comprehensiveness of several commonly used precision medicine software options currently available. Our analysis categorized selected genomic databases based on their primary content, utility, and how well they provide practical guidance for interpreting somatic biomarker data. We identified several comprehensive, mostly open-access platforms that are easy to use for genetic biomarker searches, each with unique features and limitations. Among the precision oncology tools we evaluated, we found MyCancerGenome and OncoKB to be the first choice, offering comprehensive, accurate up-to-date information on the clinical significance of somatic mutations. To illustrate the application of these precision oncology tools in clinical settings, we evaluated three case studies to see how use of the platforms could have influenced treatment planning. Most of the precision oncology software evaluated could be easily streamlined into clinical workflows to provide updated information on approved drugs and clinical trials related the actionable mutations detected. Some platforms were very intuitive and easy to use, while others, often developed in smaller academic settings, were more difficult to navigate and may not be updated consistently. Future enhancements, incorporating artificial intelligence algorithms, are likely to improve integration of the platforms with diverse big data sources, enabling more accurate predictions of potential therapeutic responses.