Overview of Next-Generation Sequencing Technologies

scIALM: A method for sparse scRNA-seq expression matrix imputation using the Inexact Augmented Lagrange Multiplier with low error

Single-cell RNA sequencing (scRNA-seq) is a high-throughput sequencing technology that quantifies gene expression profiles of specific cell populations at the single-cell level, providing a foundation for studying cellular heterogeneity and patient pathological characteristics. It is effective for developmental, fertility, and disease studies. However, the cell-gene expression matrix of single-cell sequencing data is often sparse and contains numerous zero values. Some of the zero values derive from noise, where dropout noise has a large impact on downstream analysis. In this paper, we propose a method named scIALM for imputation recovery of sparse single-cell RNA data expression matrices, which employs the Inexact Augmented Lagrange Multiplier method to use sparse but clean (accurate) data to recover unknown entries in the matrix. We perform experimental analysis on four datasets, calling the expression matrix after Quality Control (QC) as the original matrix, and comparing the performance of scIALM with six other methods using mean squared error (MSE), mean absolute error (MAE), Pearson correlation coefficient (PCC), and cosine similarity (CS). Our results demonstrate that scIALM accurately recovers the original data of the matrix with an error of 10e-4, and the mean value of the four metrics reaches 4.5072 (MSE), 0.765 (MAE), 0.8701 (PCC), 0.8896 (CS). In addition, at 10%-50% random masking noise, scIALM is the least sensitive to the masking ratio. For downstream analysis, this study uses adjusted rand index (ARI) and normalized mutual information (NMI) to evaluate the clustering effect, and the results are improved on three datasets containing real cluster labels.

A survey of k-mer methods and applications in bioinformatics

The rapid progression of genomics and proteomics has been driven by the advent of advanced sequencing technologies, large, diverse, and readily available omics datasets, and the evolution of computational data processing capabilities. The vast amount of data generated by these advancements necessitates efficient algorithms to extract meaningful information. K-mers serve as a valuable tool when working with large sequencing datasets, offering several advantages in computational speed and memory efficiency and carrying the potential for intrinsic biological functionality. This review provides an overview of the methods, applications, and significance of k-mers in genomic and proteomic data analyses, as well as the utility of absent sequences, including nullomers and nullpeptides, in disease detection, vaccine development, therapeutics, and forensic science. Therefore, the review highlights the pivotal role of k-mers in addressing current genomic and proteomic problems and underscores their potential for future breakthroughs in research.

WGS of intrauterine E. coli from cows with early postpartum uterine infection reveals a non-uterine specific genotype and virulence factors

Escherichia coli has been attributed to playing a major role in a cascade of events that affect the prevalence and severity of uterine disease in cattle. The objectives of this project were to (i) define the association between the prevalence of specific antimicrobial resistance and virulence factor genes in E. coli with the clinical status related to uterine infection, (ii) identify the genetic relationship between E. coli isolates from cows with diarrhea, with mastitis, and with and without metritis, and (iii) determine the association between the phenotypic and genotypic antimicrobial resistance identified on the E. coli isolated from postpartum cattle. Bacterial isolates (n = 148) were obtained from a larger cross-sectional study. Cows were categorized into one of three clinical groups before enrollment: metritis, cows with purulent discharge, and control cows. For genomic comparison, public genomes (n = 130) from cows with diarrhea, mastitis, and metritis were included in a genome-wide association study, to evaluate differences between the drug classes or the virulence factor category among clinical groups. A distinct E. coli genotype associated with metritis could not be identified. Instead, a high genetic diversity among the isolates from uterine sources was present. A virulence factor previously associated with metritis (fimH) using PCR was not associated with metritis. There was moderate accuracy for whole-genome sequencing to predict phenotypic resistance, which varied depending on the antimicrobial tested. Findings from this study contradict the traditional pathotype classification and the unique intrauterine E. coli genotype associated with metritis in dairy cows.IMPORTANCEMetritis is a common infectious disease in dairy cattle and the second most common reason for treating a cow with antimicrobials. The pathophysiology of the disease is complex and is not completely understood. Specific endometrial pathogenic Escherichia coli have been reported to be adapted to the endometrium and sometimes lead to uterine disease. Unfortunately, the specific genomic details of the endometrial-adapted isolates have not been investigated using enough genomes to represent the genomic diversity of this organism to identify specific virulence genes that are consistently associated with disease development and severity. Results from this study provide key microbial ecological advances by elucidating and challenging accepted concepts for the role of Intrauterine E. coli in metritis in dairy cattle, especially contradicting the existence of a unique intrauterine E. coli genotype associated with metritis in dairy cows, which was not found in our study.

Understanding pulmonary hypertension: the need for an integrative metabolomics and transcriptomics approach

Pulmonary hypertension (PH), characterised by mean pulmonary arterial pressure (mPAP) >20 mm Hg at rest, is a complex pathophysiological disorder associated with multiple clinical conditions. The high prevalence of the disease along with increased mortality and morbidity makes it a global health burden. Despite major advances in understanding the disease pathophysiology, much of the underlying complex molecular mechanism remains to be elucidated. Lack of a robust diagnostic test and specific therapeutic targets also poses major challenges. This review provides a comprehensive update on the dysregulated pathways and promising candidate markers identified in PH patients using the transcriptomics and metabolomics approach. The review also highlights the need of using an integrative multi-omics approach for obtaining insight into the disease at a molecular level. The integrative multi-omics/pan-omics approach envisaged to help in bridging the gap from genotype to phenotype is outlined. Finally, the challenges commonly encountered while conducting omics-driven studies are also discussed.

Long-read sequencing for brain tumors

Brain tumors and genomics have a long-standing history given that glioblastoma was the first cancer studied by the cancer genome atlas. The numerous and continuous advances through the decades in sequencing technologies have aided in the advanced molecular characterization of brain tumors for diagnosis, prognosis, and treatment. Since the implementation of molecular biomarkers by the WHO CNS in 2016, the genomics of brain tumors has been integrated into diagnostic criteria. Long-read sequencing, also known as third generation sequencing, is an emerging technique that allows for the sequencing of longer DNA segments leading to improved detection of structural variants and epigenetics. These capabilities are opening a way for better characterization of brain tumors. Here, we present a comprehensive summary of the state of the art of third-generation sequencing in the application for brain tumor diagnosis, prognosis, and treatment. We discuss the advantages and potential new implementations of long-read sequencing into clinical paradigms for neuro-oncology patients.

Improving the diagnosis of tuberculosis: old and new laboratory tools

INTRODUCTION

Despite recent advances in diagnostic technologies and new drugs becoming available, tuberculosis (TB) remains a major global health burden. If detected early, screened for drug resistance, and fully treated, TB could be easily controlled.

AREAS COVERED

Here the authors discuss M. tuberculosis culture methods which are considered the definitive confirmation of M. tuberculosis infection, and limited advances made to build on these core elements of TB laboratory diagnosis. Literature searches showed that molecular techniques provide enhanced speed of turnaround, sensitivity, and richness of data. Sequencing of the whole genome, is becoming well established for identification and inference of drug resistance. PubMed® literature searches were conducted (November 2022-March 2024).

EXPERT OPINION

This section highlights future advances in diagnosis and infection control. Prevention of prolonged hospital admissions and rapid TAT are of the most benefit to the overall patient experience. Host transcriptional blood markers have been used in treatment monitoring studies and, with appropriate evaluation, could be rolled out in a diagnostic setting. Additionally, the MBLA is being incorporated into latest clinical trial designs. Whole genome sequencing has enhanced epidemiological evidence. Artificial intelligence, along with machine learning, have the ability to revolutionize TB diagnosis and susceptibility testing within the next decade.

Construction of Immune Infiltration-Related LncRNA Signatures Based on Machine Learning for the Prognosis in Colon Cancer

Colon cancer is one of the malignant tumors with high morbidity, lethality, and prevalence across global human health. Molecular biomarkers play key roles in its prognosis. In particular, immune-related lncRNAs (IRL) have attracted enormous interest in diagnosis and treatment, but less is known about their potential functions. We aimed to investigate dysfunctional IRL and construct a risk model for improving the outcomes of patients. Nineteen immune cell types were collected for identifying house-keeping lncRNAs (HKLncRNA). GSE39582 and TCGA-COAD were treated as the discovery and validation datasets, respectively. Four machine learning algorithms (LASSO, Random Forest, Boruta, and Xgboost) and a Gaussian mixture model were utilized to mine the optimal combination of lncRNAs. Univariate and multivariate Cox regression was utilized to construct the risk score model. We distinguished the functional difference in an immune perspective between low- and high-risk cohorts calculated by this scoring system. Finally, we provided a nomogram. By leveraging the microarray, sequencing, and clinical data for immune cells and colon cancer patients, we identified the 221 HKLncRNAs with a low cell type-specificity index. Eighty-seven lncRNAs were up-regulated in the immune compared to cancer cells. Twelve lncRNAs were beneficial in improving performance. A risk score model with three lncRNAs (CYB561D2, LINC00638, and DANCR) was proposed with robust ROC performance on an independent dataset. According to immune-related analysis, the risk score is strongly associated with the tumor immune microenvironment. Our results emphasized IRL has the potential to be a powerful and effective therapy for enhancing the prognostic of colon cancer.

Noodles, the all-in-one system for on-target efficiency analysis of CRISPR guide RNAs

The efficiency of clustered regularly interspaced short palindromic repeats (CRISPR) guide RNA (gRNA) targeting is critical for CRISPR associated protein 9 (Cas9)-dependent genomic modifications. Here, we developed Noodles, an all-in-one system to test the on-target activity of gRNAs easily and efficiently. Single-strand annealing repair mechanism of the split luciferase gene allows a positive selection of gRNAs efficiently driving nuclease activity of Cas9 from Streptococcus pyogenes (SpCas9). Our system can reliably validate in silico-predicted gRNAs before implementing them for in vitro and in vivo applications. Altogether, Noodles might be an asset for researchers and bioengineers, saving their time and efforts, while keeping the screening efficient and sensitive. •All-in-one dual-luciferase system to easily probe on-target activity of gRNAs based on homology-directed repair mechanism.•Easy-to-subclone spCas9-based 2-plasmid system comprising Renilla luciferase for transfection efficiency control.

Diagnostic yield of repeat genetic testing in idiopathic chronic pancreatitis

Genetic testing is performed for unexplained pancreatitis. The aim of this study was to evaluate the diagnostic value of repeating genetic testing in idiopathic pancreatitis when new predisposing genes are identified. We investigated 330 patients who were initially screened for PRSS1, SPINK1 and CFTR genes. A new analysis was performed by Next-Generation Sequencing (NGS) for PRSS1, SPINK1, CFTR, CTRC, CASR, CPA1, TRPV6 genes and the CEL-HYB1 allele in clinical practice, and patients were included in our cohort study. Additional rare variants were identified in 7.3 % of the patients. Screening for new pancreatitis genes is recommended when initial screening is limited. Routine use of NGS is a useful diagnostic tool in these cases.

Design and Evaluation of a Robust CRISPR Kinetic Assay for Hot-Spot Genotyping

Next-generation sequencing offers highly multiplexed and accurate detection of nucleic acid sequences but at the expense of complex workflows and high input requirements. The ease of use of CRISPR-Cas12 assays is attractive and may enable highly accurate detection of sequences implicated in, for example, cancer pathogenic variants. CRISPR assays often employ end-point measurements of Cas12 trans-cleavage activity after Cas12 activation by the target; however, end point-based methods can be limited in accuracy and robustness by arbitrary experimental choices. To overcome such limitations, we develop and demonstrate here an accurate assay targeting a mutation of the epidermal growth factor gene implicated in lung cancer (exon 19 deletion). The assay is based on characterizing the kinetics of Cas12 trans-cleavage to discriminate the mutant from wild-type targets. We performed extensive experiments (780 reactions) to calibrate key assay design parameters, including the guide RNA sequence, reporter sequence, reporter concentration, enzyme concentration, and DNA target type. Interestingly, we observed a competitive reaction between the target and reporter molecules that has important consequences for the design of CRISPR assays, which use preamplification to improve sensitivity. Finally, we demonstrate the assay on 18 tumor-extracted amplicons and 100 training iterations with 99% accuracy and discuss discrimination parameters and models to improve wild type versus mutant classification.

Exploring Disease Resistance in Pepper (Capsicum spp.) Germplasm Collection Using Fluidigm SNP Genotyping

This study utilized a diverse Capsicum accessions (5658) sourced from various species and geographical regions, deposited at the National Agrobiodiversity Center, Genebank. We employed 19 SNP markers through a Fluidigm genotyping system and screened these accessions against eight prevalent diseases of pepper. This study revealed accessions resistant to individual diseases as well as those exhibiting resistance to multiple diseases, including bacterial spot, anthracnose, powdery mildew, phytophthora root rot, and potyvirus. The C. chacoense accessions were identified as resistant materials against bacterial spot, anthracnose, powdery mildew, and phytophthora root rot, underscoring the robust natural defense mechanisms inherent in the wild Capsicum species and its potential uses as sources of resistance for breeding. C. baccatum species also demonstrated to be a promising source of resistance to major pepper diseases. Generally, disease-resistant germplasm has been identified from various Capsicum species. Originating from diverse locations such as Argentina, Bolivia, and the United Kingdom, these accessions consistently demonstrated resistance, indicating the widespread prevalence of disease-resistant traits across varied environments. Additionally, we selected ten pepper accessions based on their resistance to multiple diseases, including CMV, Phytophthora root rot, potyviruses, and TSWV, sourced from diverse geographical regions like Hungary, Peru, the United States, and the Netherlands. This comprehensive analysis provides valuable insights into disease resistance in Capsicum, crucial for fostering sustainable agricultural practices and advancing crop improvement through breeding strategies.

An evolution of Nanopore next-generation sequencing technology: implications for medical microbiology and public health

Next-generation sequencing has evolved as a powerful tool, with applications that extend from diagnosis to public health surveillance and outbreak investigations. Short-read sequencing, using primarily Illumina chemistry, has been the prevailing approach. Single-molecule sensing and long-read sequencing using Oxford Nanopore Technologies (ONT) has witnessed a breakthrough in the evolution of the technology, performance, and applications in the past few years. In this issue of the Journal of Clinical Microbiology, Bogaerts et al. (https://doi.org/10.1128/jcm.01576-23) describe the utility of the latest ONT sequencing technology, the R10.4.1, in bacterial outbreak investigations. The authors demonstrate that ONT R10.4.1 technology can be comparable to Illumina sequencing for single-nucleotide polymorphism-based phylogeny. The authors emphasize that the reproducibility between ONT and Illumina technologies could facilitate collaborations among laboratories utilizing different sequencing platforms for outbreak investigations.

A new genetic diagnosis strategy for paroxysmal kinesigenic dyskinesia: Targeted high-throughput detection of PRRT2 gene c.649 locus

BACKGROUND

Paroxysmal kinesigenic dyskinesia (PKD) is the most prevalent kind type of paroxysmal Dyskinesia, characterized by recurrent and transient episodes of involuntary movements. Most PKD cases were attributed to the proline-rich transmembrane protein 2 (PRRT2) gene, in which the c.649 region is a hotspot for known mutations. Even though some patients with PKD have been genetically diagnosed using whole-exome sequencing (WES) and Sanger sequencing, there are still cases of missed diagnoses due to the limitations of sequencing technology and analytic methods on throughput.

METHODS

Patients meeting the diagnosis criteria of PKD with negative results of PRRT2-Sanger sequencing and WES were included in this study. Mutation screening and targeted high-throughput sequencing were performed to analyze and verify the sequencing results of the potential mutations.

RESULTS

Six patients with PKD with high mutation ratios of c.649dupC were screened using our targeted high-throughput sequencing from 26 PKD patients with negative results of PRRT2-Sanger sequencing and WES (frequency = 23.1%), which compensated for the comparatively shallow sequencing depth and statistical flaws in this region. Compared with the local normal population and other patients with PKD, the mutation ratios of c.649dupC of these six patients with PKD were much higher and also had truncated protein structures and differentially altered mRNA expression.

CONCLUSION

Based on the above studies, we emphasize the routine targeted high-throughput sequencing of the c.649 site in the PRRT2 gene in so-called genetic-testing-negative patients with PKD, and manually calculate the deletion and duplication mutations depth and ratios to lower the rate of clinical misdiagnosis.

A complete pipeline enables haplotyping and phasing macrohaplotype in long sequencing reads for polyploidy samples and a multi-source DNA mixture

Macrohaplotype combines multiple types of phased DNA variants, increasing forensic discrimination power. High-quality long-sequencing reads, for example, PacBio HiFi reads, provide data to detect macrohaplotypes in multiploidy and DNA mixtures. However, the bioinformatics tools for detecting macrohaplotypes are lacking. In this study, we developed a bioinformatics software, MacroHapCaller, in which targeted loci (i.e., short TRs [STRs], single nucleotide polymorphisms, and insertion and deletions) are genotyped and combined with novel algorithms to call macrohaplotypes from long reads. MacroHapCaller uses physical phasing (i.e., read-backed phasing) to identify macrohaplotypes, and thus it can detect multi-allelic macrohaplotypes for a given sample. MacroHapCaller was validated with data generated from our designed targeted PacBio HiFi sequencing pipeline, which sequenced ∼8-kb amplicon regions harboring 20 core forensic STR loci in human benchmark samples HG002 and HG003. MacroHapCaller also was validated in whole-genome long-read sequencing data. Robust and accurate genotyping and phased macrohaplotypes were obtained with MacroHapCaller compared with the known ground truth. MacroHapCaller achieved a higher or consistent genotyping accuracy and faster speed than existing tools HipSTR and DeepVar. MacroHapCaller enables efficient macrohaplotype analysis from high-throughput sequencing data and supports applications using discriminating macrohaplotypes.

A case study to engage students in the research design and ethics of high-throughput metagenomics

Case studies present students with an opportunity to learn and apply course content through problem solving and critical thinking. Supported by the High-throughput Discovery Science & Inquiry-based Case Studies for Today's Students (HITS) Research Coordination Network, our interdisciplinary team designed, implemented, and assessed two case study modules entitled "You Are What You Eat." Collectively, the case study modules present students with an opportunity to engage in experimental research design and the ethical considerations regarding microbiome research and society. In this manuscript, we provide instructors with tools for adopting or adapting the research design and/or the ethics modules. To date, the case has been implemented using two modalities (remote and in-person) in three courses (Microbiology, Physiology, and Neuroscience), engaging over 200 undergraduate students. Our assessment data demonstrate gains in content knowledge and students' perception of learning following case study implementation. Furthermore, when reflecting on our experiences and student feedback, we identified ways in which the case study could be modified for different settings. In this way, we hope that the "You Are What You Eat" case study modules can be implemented widely by instructors to promote problem solving and critical thinking in the traditional classroom or laboratory setting when discussing next-generation sequencing and/or metagenomics research.

Microbiome and infectious disease: diagnostics to therapeutics

Over 300 years of research on the microbial world has revealed their importance in human health and disease. This review explores the impact and potential of microbial-based detection methods and therapeutic interventions, integrating research of early microbiologists, current findings, and future perspectives.

Split Pool Ligation-based Single-cell Transcriptome sequencing (SPLiT-seq) data processing pipeline comparison

BACKGROUND

Single-cell sequencing techniques are revolutionizing every field of biology by providing the ability to measure the abundance of biological molecules at a single-cell resolution. Although single-cell sequencing approaches have been developed for several molecular modalities, single-cell transcriptome sequencing is the most prevalent and widely applied technique. SPLiT-seq (split-pool ligation-based transcriptome sequencing) is one of these single-cell transcriptome techniques that applies a unique combinatorial-barcoding approach by splitting and pooling cells into multi-well plates containing barcodes. This unique approach required the development of dedicated computational tools to preprocess the data and extract the count matrices. Here we compare eight bioinformatic pipelines (alevin-fry splitp, LR-splitpipe, SCSit, splitpipe, splitpipeline, SPLiTseq-demultiplex, STARsolo and zUMI) that have been developed to process SPLiT-seq data. We provide an overview of the tools, their computational performance, functionality and impact on downstream processing of the single-cell data, which vary greatly depending on the tool used.

RESULTS

We show that STARsolo, splitpipe and alevin-fry splitp can all handle large amount of data within reasonable time. In contrast, the other five pipelines are slow when handling large datasets. When using smaller dataset, cell barcode results are similar with the exception of SPLiTseq-demultiplex and splitpipeline. LR-splitpipe that is originally designed for processing long-read sequencing data is the slowest of all pipelines. Alevin-fry produced different down-stream results that are difficult to interpret. STARsolo functions nearly identical to splitpipe and produce results that are highly similar to each other. However, STARsolo lacks the function to collapse random hexamer reads for which some additional coding is required.

CONCLUSION

Our comprehensive comparative analysis aids users in selecting the most suitable analysis tool for efficient SPLiT-seq data processing, while also detailing the specific prerequisites for each of these pipelines. From the available pipelines, we recommend splitpipe or STARSolo for SPLiT-seq data analysis.

Genomic analysis of seven mycobacteriophages identifies three novel species with differing phenotypic stabilities

Recently, case studies have been published regarding the application of mycobacteriophage (MP) therapy (MPT) in patients with multi-antibiotic-resistant infections. A major limitation in the development of MPT is the paucity of therapeutically useful MP. As there are approximately 10,000 MP that have yet to be sequenced, it is possible that characterization of this cohort would increase the repertoire of useful MP. This study aims to contribute to such a strategy, by characterizing a cohort of 7 mycobacteriophages. Sequencing analyses revealed that the MP have unique sequences, and subsequent gene annotation revealed differences in gene organization. Notably, MP LOCARD has the largest genome and operons encoding for glycosyltransferases. Taxonomic analysis executed with VIRIDIC, Gegenees and VICTOR revealed that LOCARD belongs to a different genus than the other phages and is the foundational member of one of three novel species identified in this study. LOCARD, LOCV2, and LOCV5 were selected as representative members of their species and subjected to phenotypic analyses to compare their stability under biologically and industrially relevant conditions. Again LOCARD stood out, as it was unaffected by the typical temperatures (37 °C) and salinity (0.9%) experienced in mammals, while the viability of LOCV2 and LOCV5 was significantly reduced. LOCARD was also tolerant to pH 10, low levels of antiviral detergent and was the least impacted by a single freeze-thaw cycle. When all these results are considered, it indicates that LOCARD in particular, has potential therapeutic and/or diagnostics applications, given its resilience towards physiological and storage conditions.

Sudden Infant Death Syndrome (SIDS): State of the Art and Future Directions

Sudden infant death syndrome (SIDS) is a type of death that occurs suddenly and without any apparent explanation, affecting infants between 28 days of life and up to a year. Recognition of this entity includes performing an autopsy to determine if there is another explanation for the event and performing both an external and internal examination of the different tissues to search for possible histopathological findings. Despite the relative success of awareness campaigns and the implementation of prevention measures, SIDS still represents one of the leading causes of death among infants worldwide. In addition, although the development of different techniques has made it possible to make significant progress in the characterization of the etiopathogenic mechanisms underlying SIDS, there are still many unknowns to be resolved in this regard and the integrative consideration of this syndrome represents an enormous challenge to face both from a point of view scientific and medical view as humanitarian. For all these reasons, this paper aims to summarize the most relevant current knowledge of SIDS, exploring from the base the characterization and recognition of this condition, its forensic findings, its risk factors, and the main prevention measures to be implemented. Likewise, an attempt will be made to analyze the causes and pathological mechanisms associated with SIDS, as well as potential approaches and future paths that must be followed to reduce the impact of this condition.

Genetic interrogation for sequence and copy number variants in systemic lupus erythematosus

Early-onset systemic lupus erythematosus presents with a more severe disease and is associated with a greater genetic burden, especially in patients from Black, Asian or Hispanic ancestries. Next-generation sequencing techniques, notably whole exome sequencing, have been extensively used in genomic interrogation studies to identify causal disease variants that are increasingly implicated in the development of autoimmunity. This Review discusses the known casual variants of polygenic and monogenic systemic lupus erythematosus and its implications under certain genetic disparities while suggesting an age-based sequencing strategy to aid in clinical diagnostics and patient management for improved patient care.

Comparison of the optimal and suboptimal quantity of mitotype libraries using next-generation sequencing

Optimizing analysis parameters and sample input is crucial in forensic genetics methods to generate reliable results, and even more so when working with muti-copy mitochondrial DNA (mtDNA) and low-quality samples. This study compared mitotypes based on next-generation sequencing (NGS) results derived from the same samples at two different sequencing library concentrations-30 pM and 0.3 pM. Thirty femur samples from the Second World War were used as a model for poorly preserved DNA. Quantitative PCR (qPCR) method targeting 113 bp long fragment was employed to assess the quantity of mitogenomes. HID Ion Chef™ Instrument with Precision ID mtDNA Control Region Panel was used for library preparation and templating. Sequencing was performed with Ion GeneStudio™ S5 System. Reference haplotypes were determined from sequencing samples at 30 pM library input. Haplotypes were compared between optimal (30 pM) and suboptimal (0.3 pM) library inputs. Often the difference in haplotypes was length heteroplasmy, which in line with other studies shows that this type of variant is not reliable for interpretation in forensics. Excluding length variants at positions 573, 309, and 16,193, 56.7% of the samples matched, and in two samples, no sequence was obtained at suboptimal library input. The rest of the samples differed between optimal and suboptimal library input. To conclude, genotyping and analyzing low-quantity libraries derived from low-quality aged skeletonized human remains therefore must be done with caution in forensic genetics casework.

Genetic specificity study using next-generation sequencing (NGS) of peritoneal metastatic colorectal cancer compared to primary colorectal cancer

BACKGROUND

In patients with colorectal cancer, peritoneal metastases are the second most frequent metastatic lesion after liver metastases. Peritoneal metastases have a very poor prognosis, with a median survival time of 5-7 months. Currently, there is a lack of research on the genetic differences between primary colorectal cancer and peritoneal metastases. Therefore, we aimed to identify their genetic characteristics through a cancer panel test using next-generation sequencing.

OBJECTIVE

We aim to investigate the specificity of genetic variants in primary colorectal cancer and peritoneal metastases.

METHODS

We recruited patients with stage I, II, and III primary colorectal cancer and peritoneal metastases for genetic analysis using NGS. Samples were collected from patients who underwent surgery at Dankook University Hospital and consented to genetic testing. NGS was performed using a cancer panel.

RESULTS

Among 36 patients with primary cancer, TP53 gene mutation was identified the most in 25 patients (69%), followed by APC gene mutation in 19 patients (53%), and KRAS gene mutation in 17 patients (47%). In the peritoneal metastasis patient group, unlike the primary cancer patient group, KRAS gene mutations were the most common 6 patients (55%), followed by TP53 gene mutations in 4 patients (36%) and PIK3CA gene mutations in 2 patients (18%).

CONCLUSION

The small number of surgical cases of peritoneal metastases was a limitation of our sample size. Nevertheless, we identified differences in the alterations of specific genes between primary and peritoneal metastases. Acquiring additional cases and collecting more data will provide deeper insights into these cancers.

Facilitating taxonomy and phylogenetics: An informative and cost-effective protocol integrating long amplicon PCRs and third-generation sequencing

Phylogenetic inference has become a standard technique in integrative taxonomy and systematics, as well as in biogeography and ecology. DNA barcodes are often used for phylogenetic inference, despite being strongly limited due to their low number of informative sites. Also, because current DNA barcodes are based on a fraction of a single, fast-evolving gene, they are highly unsuitable for resolving deeper phylogenetic relationships due to saturation. In recent years, methods that analyse hundreds and thousands of loci at once have improved the resolution of the Tree of Life, but these methods require resources, experience and molecular laboratories that most taxonomists do not have. This paper introduces a PCR-based protocol that produces long amplicons of both slow- and fast-evolving unlinked mitochondrial and nuclear gene regions, which can be sequenced by the affordable and portable ONT MinION platform with low infrastructure or funding requirements. As a proof of concept, we inferred a phylogeny of a sample of 63 spider species from 20 families using our proposed protocol. The results were overall consistent with the results from approaches based on hundreds and thousands of loci, while requiring just a fraction of the cost and labour of such approaches, making our protocol accessible to taxonomists worldwide.

A high-throughput multilocus-amplicon sequencing panel to monitor insecticide resistance in fall armyworm (FAW) Spodoptera frugiperda (Lepidoptera: Noctuidae)

BACKGROUND

Fall armyworm (FAW), Spodoptera frugiperda, is a highly polyphagous crop pest that has spread over the world rapidly and invaded Australia in 2020. Globally, FAW has been reported to be resistant to several insecticides permitted in Australia. Timely resistance diagnosis is critical for integrated pest management-based control of FAW in Australia.

RESULTS

We developed a multi-amplicon panel by next-generation sequencing (multiamplicon-seq) to identify known insecticide resistance mutations in Australian FAW with high throughput and low cost. The panel included nine known mutations causing insecticide resistance in FAW and four gene mutations causing insecticide resistance in several insect species, not yet reported in FAW. We sequenced 36 plates (96-well) in one MiSeq flow cell with easy sequencing library preparation. We found that Australian FAW carried a very high proportion of the F290V mutation in the acetylcholinesterase (AChE) gene that causes resistance to organophosphate and carbamate insecticides. Furthermore, FAW has a GABA-activated chloride channel mutation, A301Q in the RDL gene. The sequencing-based platform provided evidence of a duplication in the AChE gene. Here several single nucleotide polymorphisms (SNPs) within the 476-bp amplicon of the AChE gene demonstrated 100% heterozygosity across samples and some individuals carried two haplotypes with the F290V mutation.

CONCLUSION

Molecular surveillance by multiamplicon-seq will increase capacity for early detection and future resistance monitoring in highly dispersed Australian FAW. It can provide timely resistance information and has the potential to play an important role in the resistance management of FAW. © 2023 Society of Chemical Industry.

Nanopore DNA sequencing technologies and their applications towards single-molecule proteomics

Sequencing of nucleic acids with nanopores has emerged as a powerful tool offering rapid readout, high accuracy, low cost and portability. This label-free method for sequencing at the single-molecule level is an achievement on its own. However, nanopores also show promise for the technologically even more challenging sequencing of polypeptides, something that could considerably benefit biological discovery, clinical diagnostics and homeland security, as current techniques lack portability and speed. Here we survey the biochemical innovations underpinning commercial and academic nanopore DNA/RNA sequencing techniques, and explore how these advances can fuel developments in future protein sequencing with nanopores.

Understanding gut microbiome-based machine learning platforms: A review on therapeutic approaches using deep learning

Human beings possess trillions of microbial cells in a symbiotic relationship. This relationship benefits both partners for a long time. The gut microbiota helps in many bodily functions from harvesting energy from digested food to strengthening biochemical barriers of the gut and intestine. But the changes in microbiota composition and bacteria that can enter the gastrointestinal tract can cause infection. Several approaches like culture-independent techniques such as high-throughput and meta-omics projects targeting 16S ribosomal RNA (rRNA) sequencing are popular methods to investigate the composition of the human gastrointestinal tract microbiota and taxonomically characterizing microbial communities. The microbiota conformation and diversity should be provided by whole-genome shotgun metagenomic sequencing of site-specific community DNA associating genome mapping, gene inventory, and metabolic remodelling and reformation, to ease the functional study of human microbiota. Preliminary examination of the therapeutic potency for dysbiosis-associated diseases permits investigation of pharmacokinetic-pharmacodynamic changes in microbial communities for escalation of treatment and dosage plan. Gut microbiome study is an integration of metagenomics which has influenced the field in the last two decades. And the incorporation of artificial intelligence and deep learning through "omics-based" methods and microfluidic evaluation enhanced the capability of identification of thousands of microbes.

A 25-year odyssey of genomic technology advances and structural variant discovery

This perspective focuses on advances in genome technology over the last 25 years and their impact on germline variant discovery within the field of human genetics. The field has witnessed tremendous technological advances from microarrays to short-read sequencing and now long-read sequencing. Each technology has provided genome-wide access to different classes of human genetic variation. We are now on the verge of comprehensive variant detection of all forms of variation for the first time with a single assay. We predict that this transition will further transform our understanding of human health and biology and, more importantly, provide novel insights into the dynamic mutational processes shaping our genomes.

One-pot DTECT enables rapid and efficient capture of genetic signatures for precision genome editing and clinical diagnostics

The detection of genomic sequences and their alterations is crucial for basic research and clinical diagnostics. However, current methodologies are costly and time-consuming and require outsourcing sample preparation, processing, and analysis to genomic companies. Here, we establish One-pot DTECT, a platform that expedites the detection of genetic signatures, only requiring a short incubation of a PCR product in an optimized one-pot mixture. One-pot DTECT enables qualitative, quantitative, and visual detection of biologically relevant variants, such as cancer mutations, and nucleotide changes introduced by prime editing and base editing into cancer cells and human primary T cells. Notably, One-pot DTECT achieves quantification accuracy for targeted genetic signatures comparable with Sanger and next-generation sequencing. Furthermore, its effectiveness as a diagnostic platform is demonstrated by successfully detecting sickle cell variants in blood and saliva samples. Altogether, One-pot DTECT offers an efficient, versatile, adaptable, and cost-effective alternative to traditional methods for detecting genomic signatures.

Whole Genome Sequencing: Applications in Clinical Bacteriology

The success in determining the whole genome sequence of a bacterial pathogen was first achieved in 1995 by determining the complete nucleotide sequence of Haemophilus influenzae Rd using the chain-termination method established by Sanger et al. in 1977 and automated by Hood et al. in 1987. However, this technology was laborious, costly, and time-consuming. Since 2004, high-throughput next-generation sequencing technologies have been developed, which are highly efficient, require less time, and are cost-effective for whole genome sequencing (WGS) of all organisms, including bacterial pathogens. In recent years, the data obtained using WGS technologies coupled with bioinformatics analyses of the sequenced genomes have been projected to revolutionize clinical bacteriology. WGS technologies have been used in the identification of bacterial species, strains, and genotypes from cultured organisms and directly from clinical specimens. WGS has also helped in determining resistance to antibiotics by the detection of antimicrobial resistance genes and point mutations. Furthermore, WGS data have helped in the epidemiological tracking and surveillance of pathogenic bacteria in healthcare settings as well as in communities. This review focuses on the applications of WGS in clinical bacteriology.

Insights into freshwater ciliate diversity through high throughput DNA metabarcoding

The freshwater bodies of India are highly biodiverse but still understudied, especially concerning ciliates. Ciliates constitute a significant portion of eukaryotic diversity and play crucial roles in microbial loops, nutrient recycling, and ecosystem maintenance. The present study aimed to elucidate ciliate diversity in three freshwater sites in the Delhi region of India: Okhla Bird Sanctuary (OBS), Sanjay Lake (SL), and Raj Ghat pond (RJ). This study represents the first investigation into the taxonomic diversity and richness of freshwater ciliates in India using a high-throughput DNA metabarcoding approach. For the analysis, total environmental DNA was extracted from the three freshwater samples, followed by sequencing of the 18S V4 barcode region and subsequent phylogenetic analyses. Operational taxonomic units (OTU) analyses revealed maximum species diversity in OBS (106), followed by SL (104) and RJ (99) sites. Ciliates from the classes Oligohymenophorea, Prostomatea, and Spirotrichea were dominant in the three sites. The study discusses the ability of the metabarcoding approach to uncover unknown and rare species. The study highlights the need for refined reference databases and cautious interpretation of the high-throughput sequencing-generated data while emphasizing the complementary nature of molecular and morphological approaches in studying ciliate diversity.

"Evaluating the Benefits and Limits of Multiple Displacement Amplification with Whole-Genome Oxford Nanopore Sequencing"

Multiple Displacement Amplification (MDA) outperforms conventional PCR in long fragment and whole genome amplification which makes it attractive to couple with long-read sequencing of samples with limited quantities of DNA to obtain improved genome assemblies. Here, we explore the efficacy and limits of MDA for genome sequence assembly using Oxford Nanopore Technologies (ONT) rapid library preparations and minION sequencing. We successfully generated almost complete genome sequences for all organisms examined, including Cryptosporidium meleagridis, Staphylococcus aureus, Enterococcus faecium, and Escherichia coli, with the ability to generate high-quality data from samples starting with only 0.025 ng of total DNA. Controlled sheared DNA samples exhibited a distinct pattern of size-increase after MDA, which may be associated with the amplification of long, low-abundance fragments present in the assay, as well as generating concatemeric sequences during amplification. To address concatemers, we developed a computational pipeline (CADECT: Concatemer Detection Tool) to identify and remove putative concatemeric sequences. This study highlights the efficacy of MDA in generating high-quality genome assemblies from limited amounts of input DNA. Also, the CADECT pipeline effectively mitigated the impact of concatemeric sequences, enabling the assembly of contiguous sequences even in cases where the input genomic DNA was degraded. These results have significant implications for the study of organisms that are challenging to culture in vitro, such as Cryptosporidium, and for expediting critical results in clinical settings with limited quantities of available genomic DNA.

The application of high-throughput sequencing technology in corneal diseases

High-throughput sequencing technology, also known as next-generation sequencing technology, can explore new biomarkers and specific gene mutations. It has a pivotal role in promoting the gene research, which can limit the detection area, lessen the time needed for sequencing. Also, it can quickly screen out the suspected pathogenic genes of patients, gain the necessary genetic data, and provide the basis for clinical diagnosis and genetic counseling. In the research of corneal diseases, through the DNA sequencing of patients' diseased cells, it can provide a deeper understanding of corneal diseases and improve the diagnosis, classification and treatment alternatives of various corneal diseases. This article will introduce the application progress of high-throughput sequencing technology in corneal diseases, which will help to understand the application of this technology in various corneal diseases.

HIV-1 Drug Resistance Detected by Next-Generation Sequencing among ART-Naïve Individuals: A Systematic Review and Meta-Analysis

BACKGROUND

There are an increasing number of articles focused on the prevalence and clinical impact of pretreatment HIV drug resistance (PDR) detected by Sanger sequencing (SGS). PDR may contribute to the increased likelihood of virologic failure and the emergence of new resistance mutations. As SGS is gradually replaced by next-generation sequencing (NGS), it is necessary to assess the levels of PDR using NGS in ART-naïve patients systematically. NGS can detect the viral variants (low-abundance drug-resistant HIV-1 variants (LA-DRVs)) of virus quasi-species at levels below 20% that SGS may fail to detect. NGS has the potential to optimize current HIV drug resistance surveillance methods and inform future research directions. As the NGS technique has high sensitivity, it is highly likely that the level of pretreatment resistance would be underestimated using conventional techniques.

METHODS

For the systematic review and meta-analysis, we searched for original studies published in PubMed, Web of Science, Scopus, and Embase before 30 March 2023 that focused exclusively on the application of NGS in the detection of HIV drug resistance. Pooled prevalence estimates were calculated using a random effects model using the 'meta' package in R (version 4.2.3). We described drug resistance detected at five thresholds (>1%, 2%, 5%, 10%, and 20% of virus quasi-species). Chi-squared tests were used to analyze differences between the overall prevalence of PDR reported by SGS and NGS.

RESULTS

A total of 39 eligible studies were selected. The studies included a total of 15,242 ART-naïve individuals living with HIV. The prevalence of PDR was inversely correlated with the mutation detection threshold. The overall prevalence of PDR was 29.74% at the 1% threshold, 22.43% at the 2% threshold, 15.47% at the 5% threshold, 12.95% at the 10% threshold, and 11.08% at the 20% threshold. The prevalence of PDR to INSTIs was 1.22% (95%CI: 0.58-2.57), which is the lowest among the values for all antiretroviral drugs. The prevalence of LA-DRVs was 9.45%. At the 2% and 20% detection threshold, the prevalence of PDR was 22.43% and 11.08%, respectively. Resistance to PIs and INSTIs increased 5.52-fold and 7.08-fold, respectively, in those with a PDR threshold of 2% compared with those with PDR at 20%. However, resistance to NRTIs and NNRTIs increased 2.50-fold and 2.37-fold, respectively. There was a significant difference between the 2% and 5% threshold for detecting HIV drug resistance. There was no statistically significant difference between the results reported by SGS and NGS when using the 20% threshold for reporting resistance mutations.

CONCLUSION

In this study, we found that next-generation sequencing facilitates a more sensitive detection of HIV-1 drug resistance than SGS. The high prevalence of PDR emphasizes the importance of baseline resistance and assessing the threshold for optimal clinical detection using NGS.

A novel synthetic nucleic acid mixture for quantification of microbes by mNGS

Metagenomic next-generation sequencing (mNGS) provides considerable advantages in identifying emerging and re-emerging, difficult-to-detect and co-infected pathogens; however, the clinical application of mNGS remains limited primarily due to the lack of quantitative capabilities. This study introduces a novel approach, KingCreate-Quantification (KCQ) system, for quantitative analysis of microbes in clinical specimens by mNGS, which co-sequence the target DNA extracted from the specimens along with a set of synthetic dsDNA molecules used as Internal-Standard (IS). The assay facilitates the conversion of microbial reads into their copy numbers based on IS reads utilizing a mathematical model proposed in this study. The performance of KCQ was systemically evaluated using commercial mock microbes with varying IS input amounts, different proportions of human genomic DNA, and at varying amounts of sequence analysis data. Subsequently, KCQ was applied in microbial quantitation in 36 clinical specimens including blood, bronchoalveolar lavage fluid, cerebrospinal fluid and oropharyngeal swabs. A total of 477 microbe genetic fragments were screened using the bioinformatic system. Of these 83 fragments were quantitatively compared with digital droplet PCR (ddPCR), revealing a correlation coefficient of 0.97 between the quantitative results of KCQ and ddPCR. Our study demonstrated that KCQ presents a practical approach for the quantitative analysis of microbes by mNGS in clinical samples.

Myocarditis: A multi-omics approach

Myocarditis, an inflammatory condition of weakened heart muscles often triggered by a variety of causes, that can result in heart failure and sudden death. Novel ways to enhance our understanding of myocarditis pathogenesis is available through newer modalities (omics). In this review, we examine the roles of various biomolecules and associated functional pathways across genomics, transcriptomics, proteomics, and metabolomics in the pathogenesis of myocarditis. Our analysis further explores the reproducibility and variability intrinsic to omics studies, underscoring the necessity and significance of employing a multi-omics approach to gain profound insights into myocarditis pathogenesis. This integrated strategy not only enhances our understanding of the disease, but also confirms the critical importance of a holistic multi-omics approach in disease analysis.

Application of next-generation sequencing to identify different pathogens

Early and precise detection and identification of various pathogens are essential for epidemiological monitoring, disease management, and reducing the prevalence of clinical infectious diseases. Traditional pathogen detection techniques, which include mass spectrometry, biochemical tests, molecular testing, and culture-based methods, are limited in application and are time-consuming. Next generation sequencing (NGS) has emerged as an essential technology for identifying pathogens. NGS is a cutting-edge sequencing method with high throughput that can create massive volumes of sequences with a broad application prospects in the field of pathogen identification and diagnosis. In this review, we introduce NGS technology in detail, summarizes the application of NGS in that identification of different pathogens, including bacteria, fungi, and viruses, and analyze the challenges and outlook for using NGS to identify clinical pathogens. Thus, this work provides a theoretical basis for NGS studies and provides evidence to support the application of NGS in distinguishing various clinical pathogens.

Whole Exome Sequencing as a First-Line Molecular Genetic Test in Developmental and Epileptic Encephalopathies

Developmental and epileptic encephalopathies (DEE) are severe neurodevelopmental disorders characterized by recurrent, usually early-onset, epileptic seizures accompanied by developmental impairment often related to both underlying genetic etiology and abnormal epileptiform activity. Today, next-generation sequencing technologies (NGS) allow us to sequence large portions of DNA quickly and with low costs. The aim of this study is to evaluate the use of whole-exome sequencing (WES) as a first-line molecular genetic test in a sample of subjects with DEEs characterized by early-onset drug-resistant epilepsies, associated with global developmental delay and/or intellectual disability (ID). We performed 82 WESs, identifying 35 pathogenic variants with a detection rate of 43%. The identified variants were highlighted on 29 different genes including, 3 new candidate genes (KCNC2, STXBP6, DHRS9) for DEEs never identified before. In total, 23 out of 35 (66%) de novo variants were identified. The most frequently identified type of inheritance was autosomal dominant de novo (60%) followed by autosomal recessive in homozygosity (17%) and heterozygosity (11%), autosomal dominant inherited from parental mosaicism (6%) and X-linked dominant de novo (6%). The most frequent mutations identified were missense (75%) followed by frameshift deletions (16%), frameshift duplications (5%), and splicing mutations (3%). Considering the results obtained in the present study we support the use of WES as a form of first-line molecular genetic testing in DEEs.

Management of monogenic diabetes in pregnancy: A narrative review

Pregnancy in women with monogenic diabetes is potentially complex, with significant implications for both maternal and fetal health. Among these, maturity-onset diabetes of the young (MODY) stands out as a prevalent monogenic diabetes subtype frequently encountered in clinical practice. Each subtype of MODY requires a distinct approach tailored to the pregnancy, diverging from management strategies in non-pregnant individuals. Glucokinase MODY (GCK-MODY) typically does not require treatment outside of pregnancy, but special considerations arise when a woman with GCK-MODY becomes pregnant. The glycemic targets in GCK-MODY pregnancies are not exclusively dictated by the maternal/paternal MODY genotype but are also influenced by the genotype of the developing fetus. During pregnancy, the choice between sulfonylurea or insulin for treating hepatocyte nuclear factor 1-alpha (HNF1A)-MODY and HNF4A-MODY depends on the mother's specific circumstances and the available expertise. Management of other rarer MODY subtypes is individualized, with decisions made on a case-by-case basis. Therefore, a collaborative approach involving expert diabetes and obstetric teams is crucial for the comprehensive management of MODY pregnancies.

Methylation of the Oxytocin, Oxytocin Receptor, and Vasopressin Gene Promoters in Tobacco Use Disorder during Cessation

INTRODUCTION

Vasopressin (AVP) and oxytocin (OT) exert sex-specific effects on social pair bonding and stress reactions while also influencing craving in substance use disorders. In this regard, intranasal oxytocin (OT) and AVP antagonists present potential treatments for tobacco use disorder (TUD). Since transcription of both hormones is also regulated by gene methylation, we hypothesized sex-specific changes in methylation levels of the AVP, OT, and OT receptor (OXTR) gene during nicotine withdrawal.

METHODS

The study population consisted of 49 smokers (29 males, 20 females) and 51 healthy non-smokers (25 males, 26 females). Blood was drawn at day 1, day 7, and day 14 of smoking cessation. Craving was assessed with the questionnaire on smoking urges (QSU).

RESULTS

Throughout cessation, mean methylation of the OT promoter gene increased in males and decreased in females. OXTR receptor methylation decreased in females, while in males it was significantly lower at day 7. Regarding the AVP promoter, mean methylation increased in males while there were no changes in females. Using mixed linear modeling, CpG position, time point, sex, and the interaction of time point and sex as well as time point, sex, and QSU had a significant fixed effect on OT and AVP gene methylation. The interaction effect suggests that sex, time point, and QSU are interrelated, meaning that, depending on the sex, methylation could be different at different time points and vice versa. There was no significant effect of QSU on mean OXTR methylation.

DISCUSSION

We identified differences at specific CpGs between controls and smokers in OT and AVP and in overall methylation of the AVP gene. Furthermore, we found sex-specific changes in mean methylation levels of the mentioned genes throughout smoking cessation, underlining the relevance of sex in the OT and vasopressin system. This is the first study on epigenetic regulation of the OT promoter in TUD. Our results have implications for research on the utility of the AVP and OT system for treating substance craving. Future studies on both targets need to analyze their effect in the context of sex, social factors, and gene regulation.

Next-Generation Sequencing to Study the DNA Interaction

Next-generation sequencing (NGS) has transformed genomics by allowing researchers to sequence DNA and RNA at highest speed, accuracy, and cost-effectiveness. Researchers investigate DNA interactions with the help next-generation sequencing with a great deal of information. Over the last decade, NGS technologies have advanced significantly, with the development of several platforms, including Illumina, PacBio, and Oxford Nanopore, each offering distinct advantages and uses. The use of next-generation sequencing (NGS) has aided in the discovery of genetic variations, gene expression patterns, and epigenetic modifications connected with a variety of diseases, including cancer, neurological disorders, and infectious diseases. By identifying these regions, we can control the expression of genes, cellular signaling pathways, and other key biological processes. NGS is an effective method for researching DNA interactions that has completely transformed the area of genomics. NGS has also played an important part in personalized medicine, enabling the discovery of disease-causing mutations and the creation of targeted medicines. Finally, NGS has transformed the field of genomics, resulting in new discoveries and applications in medicine, environmental sciences, and other fields.

How to make DNA data storage more applicable

The storage of digital data is becoming a worldwide problem. DNA has been recognized as a biological solution due to its ability to store genetic information without alteration over long periods. The first demonstrations of high-capacity long-lasting DNA digital data storage have been shown. However, high storage costs and slow retrieval of the data must be overcome to make DNA data storage more applicable and marketable. Herein, we discuss the issues and recent advances in DNA data storage methods and highlight pathways to make this technology more applicable to real-world digital data storage. We envision that a combination of molecular biology, nanotechnology, novel polymers, electronics, and automation with systematic development will allow DNA data storage sufficient for everyday use.

Modeling human immune responses to vaccination in vitro

The human immune system is a complex network of coordinated components that are crucial for health and disease. Animal models, commonly used to study immunomodulatory agents, are limited by species-specific differences, low throughput, and ethical concerns. In contrast, in vitro modeling of human immune responses can enable species- and population-specific mechanistic studies and translational development within the same study participant. Translational accuracy of in vitro models is enhanced by accounting for genetic, epigenetic, and demographic features such as age, sex, and comorbidity. This review explores various human in vitro immune models, considers evidence that they may resemble human in vivo responses, and assesses their potential to accelerate and de-risk vaccine discovery and development.

A Mini-review on Helicobacter pylori with Gastric Cancer and Available Treatments

Helicobacter pylori (H. pylori) is the most thoroughly researched etiological component for stomach inflammation and malignancies. Even though there are conventional recommendations and treatment regimens for eradicating H. pylori, failure rates continue to climb. Antibiotic resistance contributes significantly to misdiagnoses, false positive results, and clinical failures, all of which raise the chance of infection recurrence. This review aims to explore the molecular mechanisms underlying drug resistance in H. pylori and discuss novel approaches for detecting genotypic resistance. Modulation of drug uptake/ efflux, biofilm, and coccoid development. Newer genome sequencing approaches capable of detecting H. pylori genotypic resistance are presented. Prolonged infection in the stomach causes major problems such as gastric cancer. The review discusses how H. pylori causes stomach cancer, recent biomarkers such as miRNAs, molecular pathways in the development of gastric cancer, and diagnostic methods and clinical trials for the disease. Efforts have been made to summarize the recent advancements made toward early diagnosis and novel therapeutic approaches for H. pylori-induced gastric cancer.

Molecular Profile of Intrahepatic Cholangiocarcinoma

Intrahepatic cholangiocarcinoma (ICC) is a relatively uncommon but highly aggressive primary liver cancer that originates within the liver. The aim of this study is to review the molecular profile of intrahepatic cholangiocarcinoma and its implications for prognostication and decision-making. This comprehensive characterization of ICC tumors sheds light on the disease's underlying biology and offers a foundation for more personalized treatment strategies. This is a narrative review of the prognostic and therapeutic role of the molecular profile of ICC. Knowing the molecular profile of tumors helps determine prognosis and support certain target therapies. The molecular panel in ICC helps to select patients for specific therapies, predict treatment responses, and monitor treatment responses. Precision medicine in ICC can promote improvement in prognosis and reduce unnecessary toxicity and might have a significant role in the management of ICC in the following years. The main mutations in ICC are in tumor protein p53 (TP53), Kirsten rat sarcoma virus (KRAS), isocitrate dehydrogenase 1 (IDH1), and AT-rich interactive domain-containing protein 1A (ARID1A). The rate of mutations varies significantly for each population. Targeting TP53 and KRAS is challenging due to the natural characteristics of these genes. Different stages of clinical studies have shown encouraging results with inhibitors of mutated IDH1 and target therapy for ARID1A downstream effectors. Fibroblast growth factor receptor 2 (FGFR2) fusions are an important target in patients with ICC. Immune checkpoint blockade can be applied to a small percentage of ICC patients. Molecular profiling in ICC represents a groundbreaking approach to understanding and managing this complex liver cancer. As our comprehension of ICC's molecular intricacies continues to expand, so does the potential for offering patients more precise and effective treatments. The integration of molecular profiling into clinical practice signifies the dawn of a new era in ICC care, emphasizing personalized medicine in the ongoing battle against this malignancy.

Applications of some advanced sequencing, analytical, and computational approaches in medicinal plant research: a review

The potential active chemicals found in medicinal plants, which have long been employed as natural medicines, are abundant. Exploring the genes responsible for producing these compounds has given new insights into medicinal plant research. Previously, the authentication of medicinal plants was done via DNA marker sequencing. With the advancement of sequencing technology, several new techniques like next-generation sequencing, single molecule sequencing, and fourth-generation sequencing have emerged. These techniques enshrined the role of molecular approaches for medicinal plants because all the genes involved in the biosynthesis of medicinal compound(s) could be identified through RNA-seq analysis. In several research insights, transcriptome data have also been used for the identification of biosynthesis pathways. miRNAs in several medicinal plants and their role in the biosynthesis pathway as well as regulation of the disease-causing genes were also identified. In several research articles, an in silico study was also found to be effective in identifying the inhibitory effect of medicinal plant-based compounds against virus' gene(s). The use of advanced analytical methods like spectroscopy and chromatography in metabolite proofing of secondary metabolites has also been reported in several recent research findings. Furthermore, advancement in molecular and analytic methods will give new insight into studying the traditionally important medicinal plants that are still unexplored.

A novel assay based on DNA melting temperature for multiplexed identification of SARS-CoV-2 and influenza A/B viruses

Introduction

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) and influenza viruses can cause respiratory illnesses with similar clinical symptoms, making their differential diagnoses challenging. Additionally, in critically ill SARS-CoV-2-infected patients, co-infections with other respiratory pathogens can lead to severe cytokine storm and serious complications. Therefore, a method for simultaneous detection of SARS-CoV-2 and influenza A and B viruses will be clinically beneficial.

Methods

We designed an assay to detect five gene targets simultaneously via asymmetric PCR-mediated melting curve analysis in a single tube. We used specific probes that hybridize to corresponding single-stranded amplicons at low temperature and dissociate at high temperature, creating different detection peaks representing the targets. The entire reaction was conducted in a closed tube, which minimizes the risk of contamination. The limit of detection, specificity, precision, and accuracy were determined.

Results

The assay exhibited a limit of detection of <20 copies/μL for SARS-CoV-2 and influenza A and <30 copies/μL for influenza B, with high reliability as demonstrated by a coefficient of variation for melting temperature of <1.16% across three virus concentrations. The performance of our developed assay and the pre-determined assay showed excellent agreement for clinical samples, with kappa coefficients ranging from 0.98 (for influenza A) to 1.00 (for SARS-CoV-2 and influenza B). No false-positive, and no cross-reactivity was observed with six common non-influenza respiratory viruses.

Conclusion

The newly developed assay offers a straightforward, cost-effective and nucleic acid contamination-free approach for simultaneous detection of the SARS-CoV-2, influenza A, and influenza B viruses. The method offers high analytical sensitivity, reliability, specificity, and accuracy. Its use will streamline testing for co-infections, increase testing throughput, and improve laboratory efficacy.

GenoPipe: identifying the genotype of origin within (epi)genomic datasets

Confidence in experimental results is critical for discovery. As the scale of data generation in genomics has grown exponentially, experimental error has likely kept pace despite the best efforts of many laboratories. Technical mistakes can and do occur at nearly every stage of a genomics assay (i.e. cell line contamination, reagent swapping, tube mislabelling, etc.) and are often difficult to identify post-execution. However, the DNA sequenced in genomic experiments contains certain markers (e.g. indels) encoded within and can often be ascertained forensically from experimental datasets. We developed the Genotype validation Pipeline (GenoPipe), a suite of heuristic tools that operate together directly on raw and aligned sequencing data from individual high-throughput sequencing experiments to characterize the underlying genome of the source material. We demonstrate how GenoPipe validates and rescues erroneously annotated experiments by identifying unique markers inherent to an organism's genome (i.e. epitope insertions, gene deletions and SNPs).

Genotype and phenotype data standardization, utilization and integration in the big data era for agricultural sciences

Large-scale genotype and phenotype data have been increasingly generated to identify genetic markers, understand gene function and evolution and facilitate genomic selection. These datasets hold immense value for both current and future studies, as they are vital for crop breeding, yield improvement and overall agricultural sustainability. However, integrating these datasets from heterogeneous sources presents significant challenges and hinders their effective utilization. We established the Genotype-Phenotype Working Group in November 2021 as a part of the AgBioData Consortium (https://www.agbiodata.org) to review current data types and resources that support archiving, analysis and visualization of genotype and phenotype data to understand the needs and challenges of the plant genomic research community. For 2021-22, we identified different types of datasets and examined metadata annotations related to experimental design/methods/sample collection, etc. Furthermore, we thoroughly reviewed publicly funded repositories for raw and processed data as well as secondary databases and knowledgebases that enable the integration of heterogeneous data in the context of the genome browser, pathway networks and tissue-specific gene expression. Based on our survey, we recommend a need for (i) additional infrastructural support for archiving many new data types, (ii) development of community standards for data annotation and formatting, (iii) resources for biocuration and (iv) analysis and visualization tools to connect genotype data with phenotype data to enhance knowledge synthesis and to foster translational research. Although this paper only covers the data and resources relevant to the plant research community, we expect that similar issues and needs are shared by researchers working on animals. Database URL: https://www.agbiodata.org.

vcfdist: accurately benchmarking phased small variant calls in human genomes

Accurately benchmarking small variant calling accuracy is critical for the continued improvement of human whole genome sequencing. In this work, we show that current variant calling evaluations are biased towards certain variant representations and may misrepresent the relative performance of different variant calling pipelines. We propose solutions, first exploring the affine gap parameter design space for complex variant representation and suggesting a standard. Next, we present our tool vcfdist and demonstrate the importance of enforcing local phasing for evaluation accuracy. We then introduce the notion of partial credit for mostly-correct calls and present an algorithm for clustering dependent variants. Lastly, we motivate using alignment distance metrics to supplement precision-recall curves for understanding variant calling performance. We evaluate the performance of 64 phased Truth Challenge V2 submissions and show that vcfdist improves measured insertion and deletion performance consistency across variant representations from R2 = 0.97243 for baseline vcfeval to 0.99996 for vcfdist.