A Comprehensive Review of Performance of Next-Generation Sequencing Platforms

Molecular methods in cancer diagnostics: a short review

BACKGROUND

One of the ailments with the greatest fatality rates in the 21st century is cancer. Globally, molecular methods are widely employed to treat cancer-related disorders, and the body of research on this subject is growing yearly. A thorough and critical summary of the data supporting molecular methods for illnesses linked to cancer is required.

OBJECTIVE

In order to guide clinical practice and future research, it is important to examine and summarize the systematic reviews (SRs) that evaluate the efficacy and safety of molecular methods for disorders associated to cancer.

METHODS

We developed a comprehensive search strategy to find relevant articles from electronic databases like PubMed, Google Scholar, Web of Science (WoS), or Scopus. We looked through the literature and determined which diagnostic methods in cancer genetics were particularly reliable. We used phrases like 'cancer genetics', genetic susceptibility, Hereditary cancer, cancer risk assessment, 'cancer diagnostic tools', cancer screening', biomarkers, and molecular diagnostics, reviews and meta-analyses evaluating the efficacy and safety of molecular therapies for cancer-related disorders. Research that only consider treatment modalities that don't necessitate genetic or molecular diagnostics fall under the exclusion criteria.

RESULTS

The results of this comprehensive review clearly demonstrate the transformative impact of molecular methods in the realm of cancer genetics.This review underscores how these technologies have empowered researchers and clinicians to identify and understand key genetic alterations that drive malignancy, ranging from point mutations to structural variations. Such insights are instrumental in pinpointing critical oncogenic drivers and potential therapeutic targets, thus opening the door for methods in precision medicine that can significantly improve patient outcomes.

LIMITATION

The search does not specify a timeframe for publication inclusion, it may have missed recent advancements or changes in the field's landscape of molecular methods for cancer. As a result, it may not have included the most recent developments in the field.

CONCLUSION

After conducting an in-depth study on the molecular methods in cancer genetics, it is evident that these cutting-edge technologies have revolutionized the field of oncology, providing researchers and clinicians with powerful tools to unravel the complexities of cancer at the genetic level. The integration of molecular methods techniques has not only enhanced our understanding of cancer etiology, progression, and treatment response but has also opened new avenues for personalized medicine and targeted therapies, leading to improved patient outcomes.

Utility analyses of AVITI sequencing chemistry

BACKGROUND

DNA sequencing is a critical tool in modern biology. Over the last two decades, it has been revolutionized by the advent of massively parallel sequencing, leading to significant advances in the genome and transcriptome sequencing of various organisms. Nevertheless, challenges with accuracy, lack of competitive options and prohibitive costs associated with high throughput parallel short-read sequencing persist.

RESULTS

Here, we conduct a comparative analysis using matched DNA and RNA short-reads assays between Element Biosciences' AVITI and Illumina's NextSeq 550 chemistries. Similar comparisons were evaluated for synthetic long-read sequencing for RNA and targeted single-cell transcripts between the AVITI and Illumina's NovaSeq 6000. For both DNA and RNA short-read applications, the study found that the AVITI produced significantly higher per sequence quality scores. For PCR-free DNA libraries, we observed an average 89.7% lower experimentally determined error rate when using the AVITI chemistry, compared to the NextSeq 550. For short-read RNA quantification, AVITI platform had an average of 32.5% lower error rate than that for NextSeq 550. With regards to synthetic long-read mRNA and targeted synthetic long read single cell mRNA sequencing, both platforms' respective chemistries performed comparably in quantification of genes and isoforms. The AVITI displayed a marginally lower error rate for long reads, with fewer chemistry-specific errors and a higher mutation detection rate.

CONCLUSION

These results point to the potential of the AVITI platform as a competitive candidate in high-throughput short read sequencing analyses when juxtaposed with the Illumina NextSeq 550.

Lessons and pitfalls of whole genome sequencing

Whole-genome sequencing (WGS) has recently become the first-line genetic investigation for many suspected genetic neurological disorders. While its diagnostic capabilities are innumerable, as with any test, it has its limitations. Clinicians should be aware of where WGS is extremely reliable (detecting single-nucleotide variants), where its reliability is much improved (detecting copy number variants and small repeat expansions) and where it may miss/misinterpret a variant (large repeat expansions, balanced structural variants or low heteroplasmy mitochondrial DNA variants). Bioinformatic technology and virtual gene panels are constantly evolving, and it is important to know what genes and what types of variant are being tested; the current National Health Service Genomic Medicine Service WGS offers more than early iterations of the 100 000 Genomes Project analysis. Close communication between clinician and laboratory, ideally through a multidisciplinary team meeting, is encouraged where there is diagnostic uncertainty.

Single-molecule detection and super-resolution imaging with a portable and adaptable 3D-printed microscopy platform (Brick-MIC)

Over the past decades, single-molecule and super-resolution microscopy have advanced and represent essential tools for life science research. There is,however, a growing gap between the state-of-the-art and what is accessible to biologists, biochemists, medical researchers or labs with financial constraints. To bridge this gap, we introduce Brick-MIC, a versatile and affordable open-source 3D-printed micro-spectroscopy and imaging platform. Brick-MIC enables the integration of various fluorescence imaging techniques with single-molecule resolution within a single platform and exchange between different modalities within minutes. We here present variants of Brick-MIC that facilitate single-molecule fluorescence detection, fluorescence correlation spectroscopy and super-resolution imaging (STORM and PAINT). Detailed descriptions of the hardware and software components, as well as data analysis routines are provided, to allow non-optics specialist to operate their own Brick-MIC with minimal effort and investments. We foresee that our affordable, flexible, and opensource Brick-MIC platform will be a valuable tool for many laboratories worldwide.

Performance evaluation of a newly developed 2019-nCoV nucleic acid detection kit based on Ion Proton sequencing platform and its comparison with the MGI Tech (DNBSEQ-G99) platform

PURPOSE

To evaluate the performance of a newly developed 2019-nCoV nucleic acid detection kit based on Ion Proton sequencing platform and make comparation with MGI Tech (DNBSEQ-G99) platform.

METHODS

References and clinical samples were used to evaluate the precision, agreement rate, limit of detection (LOD), anti-interference ability and analytical specificity. Twenty-seven clinical specimens were used to make comparison between two platforms.

RESULTS

The kit showed good intra-assay, inter-assay, inter-day precision between different operators and laboratories, fine agreement rate with references, a relatively low LOD of 1 × 103 copies/ml, anti-interference capability of 5 % whole blood and 1mg/ml mucin and no cross reaction with twenty-nine common clinical pathogens. Consistency of variant classification was observed between two platforms. The WGS from Ion Proton tended to have higher coverage and less missing data.

CONCLUSIONS

The newly developed kit has shown satisfactory performances and excellent consistency with DNBSEQ-G99, making it a good alternative choice clinically.

Assessing ChatGPT's Responses to Otolaryngology Patient Questions

OBJECTIVE

This study aims to evaluate ChatGPT's performance in addressing real-world otolaryngology patient questions, focusing on accuracy, comprehensiveness, and patient safety, to assess its suitability for integration into healthcare.

METHODS

A cross-sectional study was conducted using patient questions from the public online forum Reddit's r/AskDocs, where medical advice is sought from healthcare professionals. Patient questions were input into ChatGPT (GPT-3.5), and responses were reviewed by 5 board-certified otolaryngologists. The evaluation criteria included difficulty, accuracy, comprehensiveness, and bedside manner/empathy. Statistical analysis explored the relationship between patient question characteristics and ChatGPT response scores. Potentially dangerous responses were also identified.

RESULTS

Patient questions averaged 224.93 words, while ChatGPT responses were longer at 414.93 words. The accuracy scores for ChatGPT responses were 3.76/5, comprehensiveness scores were 3.59/5, and bedside manner/empathy scores were 4.28/5. Longer patient questions did not correlate with higher response ratings. However, longer ChatGPT responses scored higher in bedside manner/empathy. Higher question difficulty correlated with lower comprehensiveness. Five responses were flagged as potentially dangerous.

CONCLUSION

While ChatGPT exhibits promise in addressing otolaryngology patient questions, this study demonstrates its limitations, particularly in accuracy and comprehensiveness. The identification of potentially dangerous responses underscores the need for a cautious approach to AI in medical advice. Responsible integration of AI into healthcare necessitates thorough assessments of model performance and ethical considerations for patient safety.

How to overcome constraints imposed by microsporidian genome features to ensure gene prediction?

Since the advent of sequencing techniques and due to their continuous evolution, it has become easier and less expensive to obtain the complete genome sequence of any organism. Nevertheless, to elucidate all biological processes governing organism development, quality annotation is essential. In genome annotation, predicting gene structure is one of the most important and captivating challenges for computational biology. This aspect of annotation requires continual optimization, particularly for genomes as unusual as those of microsporidia. Indeed, this group of fungal-related parasites exhibits specific features (highly reduced gene sizes, sequences with high rate of evolution) linked to their evolution as intracellular parasites, requiring the implementation of specific annotation approaches to consider all these features. This review aimed to outline these characteristics and to assess the increasingly efficient approaches and tools that have enhanced the accuracy of gene prediction for microsporidia, both in terms of sensitivity and specificity. Subsequently, a final part will be dedicated to postgenomic approaches aimed at reinforcing the annotation data generated by prediction software. These approaches include the characterization of other understudied genes, such as those encoding regulatory noncoding RNAs or very small proteins, which also play crucial roles in the life cycle of these microorganisms.

Metagenomics approaches in unveiling the dynamics of Plant Growth-Promoting Microorganisms (PGPM) vis-à-vis Phytophthora sp. suppression in various crop ecological systems

Phytophthora species are destructive pathogens causing yield losses in different ecological systems, such as potato, black pepper, pepper, avocado, citrus, and tobacco. The diversity of plant growth-promoting microorganisms (PGPM) plays a crucial role in disease suppression. Knowledge of metagenomics approaches is essential for assessing the dynamics of PGPM and Phytophthora species across various ecosystems, facilitating effective management strategies for better crop protection. This review discusses the dynamic interplay between PGPM and Phytophthora sp. using metagenomics approaches that sheds light on the potential of PGPM strains tailored to specific crop ecosystems to bolster pathogen suppressiveness.

Exome and genome sequencing in a heterogeneous population of patients with rare disease: Identifying predictors of a diagnosis

PURPOSE

Exome (ES) and genome sequencing (GS) are increasingly being utilized for individuals with rare and undiagnosed diseases; however, guidelines on their use remain limited. This study aimed to identify factors associated with diagnosis by ES and/or GS in a heterogeneous population of patients with rare and undiagnosed diseases.

METHODS

In this case control study, we reviewed data from 400 diagnosed and 400 undiagnosed randomly selected participants in the Undiagnosed Diseases Network, all of whom had undergone ES and/or GS. We analyzed factors associated with receiving a diagnosis by ES and/or GS.

RESULTS

Factors associated with a decreased odds of being diagnosed included adult symptom onset, singleton sequencing, and having undergone ES and/or GS before acceptance to the Undiagnosed Diseases Network (48%, 51%, and 32% lower odds, respectively). Factors that increased the odds of being diagnosed by ES and/or GS included having primarily neurological symptoms and having undergone prior chromosomal microarray testing (44% and 59% higher odds, respectively).

CONCLUSION

We identified several factors that were associated with receiving a diagnosis by ES and/or GS. This will ideally inform the utilization of ES and/or GS and help manage expectations of individuals and families undergoing these tests.

Spatiotemporal multi-omics: exploring molecular landscapes in aging and regenerative medicine

Aging and regeneration represent complex biological phenomena that have long captivated the scientific community. To fully comprehend these processes, it is essential to investigate molecular dynamics through a lens that encompasses both spatial and temporal dimensions. Conventional omics methodologies, such as genomics and transcriptomics, have been instrumental in identifying critical molecular facets of aging and regeneration. However, these methods are somewhat limited, constrained by their spatial resolution and their lack of capacity to dynamically represent tissue alterations. The advent of emerging spatiotemporal multi-omics approaches, encompassing transcriptomics, proteomics, metabolomics, and epigenomics, furnishes comprehensive insights into these intricate molecular dynamics. These sophisticated techniques facilitate accurate delineation of molecular patterns across an array of cells, tissues, and organs, thereby offering an in-depth understanding of the fundamental mechanisms at play. This review meticulously examines the significance of spatiotemporal multi-omics in the realms of aging and regeneration research. It underscores how these methodologies augment our comprehension of molecular dynamics, cellular interactions, and signaling pathways. Initially, the review delineates the foundational principles underpinning these methods, followed by an evaluation of their recent applications within the field. The review ultimately concludes by addressing the prevailing challenges and projecting future advancements in the field. Indubitably, spatiotemporal multi-omics are instrumental in deciphering the complexities inherent in aging and regeneration, thus charting a course toward potential therapeutic innovations.

Omics technology draws a comprehensive heavy metal resistance strategy in bacteria

The rapid industrial revolution significantly increased heavy metal pollution, becoming a major global environmental concern. This pollution is considered as one of the most harmful and toxic threats to all environmental components (air, soil, water, animals, and plants until reaching to human). Therefore, scientists try to find a promising and eco-friendly technique to solve this problem i.e., bacterial bioremediation. Various heavy metal resistance mechanisms were reported. Omics technologies can significantly improve our understanding of heavy metal resistant bacteria and their communities. They are a potent tool for investigating the adaptation processes of microbes in severe conditions. These omics methods provide unique benefits for investigating metabolic alterations, microbial diversity, and mechanisms of resistance of individual strains or communities to harsh conditions. Starting with genome sequencing which provides us with complete and comprehensive insight into the resistance mechanism of heavy metal resistant bacteria. Moreover, genome sequencing facilitates the opportunities to identify specific metal resistance genes, operons, and regulatory elements in the genomes of individual bacteria, understand the genetic mechanisms and variations responsible for heavy metal resistance within and between bacterial species in addition to the transcriptome, proteome that obtain the real expressed genes. Moreover, at the community level, metagenome, meta transcriptome and meta proteome participate in understanding the microbial interactive network potentially novel metabolic pathways, enzymes and gene species can all be found using these methods. This review presents the state of the art and anticipated developments in the use of omics technologies in the investigation of microbes used for heavy metal bioremediation.

New insight into genetic diversity of zoonotic-potential Ancylostoma ceylanicum in stray cats living in Bangkok, Thailand, based on deep amplicon sequencing

AIMS

This study aimed to characterize feline hookworms from stray cats living in Bangkok.

METHODS AND RESULTS

A total of 56 hookworm-positive faecal samples were identified for hookworm species by using PCR targeting the ITS1, 5.8S, and ITS2 fragment and qPCR targeting ITS2. Of 56 samples, 96.4% (54/56) were identified as Ancylostoma ceylanicum and 1.8% (1/56) as Ancylostoma caninum. With qPCR, 89.3% (50/56) were identified as single A. ceylanicum infection and 5.4% (3/56) as coinfection of A. ceylanicum and A. caninum. For genetic characterization of A. ceylanicum, 10 samples were pooled, and the partial COI gene was amplified, followed by deep amplicon sequencing. Five pooled samples were analysed, and 99.73% were identified with A. ceylanicum sequences, which were allocated into 19 haplotypes (AC01-AC19). Genetic diversity findings for A. ceylanicum in Asia revealed that three of eight haplotypes considered of zoonotic significance occurred in humans, dogs, and cats, including haplotypes H01, H20, and H21. The predominant haplotype in this study, AC01, was clustered with H01-a zoonotic haplotype.

CONCLUSIONS

The diversity obtained by deep amplicon sequencing supported that the A. ceylanicum community had high genetic variation. Deep amplicon sequencing was a useful method to determine source, zoonotic potential, and host-parasite relationship.

A novel transformer-based aggregation model for predicting gene mutations in lung adenocarcinoma

In recent years, predicting gene mutations on whole slide imaging (WSI) has gained prominence. The primary challenge is extracting global information and achieving unbiased semantic aggregation. To address this challenge, we propose a novel Transformer-based aggregation model, employing a self-learning weight aggregation mechanism to mitigate semantic bias caused by the abundance of features in WSI. Additionally, we adopt a random patch training method, which enhances model learning richness by randomly extracting feature vectors from WSI, thus addressing the issue of limited data. To demonstrate the model's effectiveness in predicting gene mutations, we leverage the lung adenocarcinoma dataset from Shandong Provincial Hospital for prior knowledge learning. Subsequently, we assess TP53, CSMD3, LRP1B, and TTN gene mutations using lung adenocarcinoma tissue pathology images and clinical data from The Cancer Genome Atlas (TCGA). The results indicate a notable increase in the AUC (Area Under the ROC Curve) value, averaging 4%, attesting to the model's performance improvement. Our research offers an efficient model to explore the correlation between pathological image features and molecular characteristics in lung adenocarcinoma patients. This model introduces a novel approach to clinical genetic testing, expected to enhance the efficiency of identifying molecular features and genetic testing in lung adenocarcinoma patients, ultimately providing more accurate and reliable results for related studies.

Optimizing Nucleic Acid Delivery Systems through Barcode Technology

Conventional biological experiments often focus on in vitro assays because of the inherent limitations when handling multiple variables in vivo, including labor-intensive and time-consuming procedures. Often only a subset of samples demonstrating significant efficacy in the in vitro assays can be evaluated in vivo. Nonetheless, because of the low correlation between the in vitro and in vivo tests, evaluation of the variables under examination in vivo and not solely in vitro is critical. An emerging approach to achieve high-throughput in vivo tests involves using a barcode system consisting of various nucleotide combinations. Unique barcodes for each variant enable the simultaneous testing of multiple entities, eliminating the need for separate individual tests. Subsequently, to identify crucial parameters, samples were collected and analyzed using barcode sequencing. This review explores the development of barcode design and its applications, including the evaluation of nucleic acid delivery systems and the optimization of gene expression in vivo.

Single-cell and spatial transcriptomics: Bridging current technologies with long-read sequencing

Single-cell technologies have transformed biomedical research over the last decade, opening up new possibilities for understanding cellular heterogeneity, both at the genomic and transcriptomic level. In addition, more recent developments of spatial transcriptomics technologies have made it possible to profile cells in their tissue context. In parallel, there have been substantial advances in sequencing technologies, and the third generation of methods are able to produce reads that are tens of kilobases long, with error rates matching the second generation short reads. Long reads technologies make it possible to better map large genome rearrangements and quantify isoform specific abundances. This further improves our ability to characterize functionally relevant heterogeneity. Here, we show how researchers have begun to combine single-cell, spatial transcriptomics, and long-read technologies, and how this is resulting in powerful new approaches to profiling both the genome and the transcriptome. We discuss the achievements so far, and we highlight remaining challenges and opportunities.

Update on the proposed minimal standards for the use of genome data for the taxonomy of prokaryotes

The field of microbial taxonomy is dynamic, aiming to provide a stable and contemporary classification system for prokaryotes. Traditionally, reliance on phenotypic characteristics limited the comprehensive understanding of microbial diversity and evolution. The introduction of molecular techniques, particularly DNA sequencing and genomics, has transformed our perception of prokaryotic diversity. In the past two decades, advancements in genome sequencing have transitioned from traditional methods to a genome-based taxonomic framework, not only to define species, but also higher taxonomic ranks. As technology and databases rapidly expand, maintaining updated standards is crucial. This work seeks to revise the 2018 guidelines for applying genome sequencing data in microbial taxonomy, adapting minimal standards and recommendations to reflect technological progress during this period.

Unraveling the Genetic Landscape of Neurological Disorders: Insights into Pathogenesis, Techniques for Variant Identification, and Therapeutic Approaches

Genetic abnormalities play a crucial role in the development of neurodegenerative disorders (NDDs). Genetic exploration has indeed contributed to unraveling the molecular complexities responsible for the etiology and progression of various NDDs. The intricate nature of rare and common variants in NDDs contributes to a limited understanding of the genetic risk factors associated with them. Advancements in next-generation sequencing have made whole-genome sequencing and whole-exome sequencing possible, allowing the identification of rare variants with substantial effects, and improving the understanding of both Mendelian and complex neurological conditions. The resurgence of gene therapy holds the promise of targeting the etiology of diseases and ensuring a sustained correction. This approach is particularly enticing for neurodegenerative diseases, where traditional pharmacological methods have fallen short. In the context of our exploration of the genetic epidemiology of the three most prevalent NDDs-amyotrophic lateral sclerosis, Alzheimer's disease, and Parkinson's disease, our primary goal is to underscore the progress made in the development of next-generation sequencing. This progress aims to enhance our understanding of the disease mechanisms and explore gene-based therapies for NDDs. Throughout this review, we focus on genetic variations, methodologies for their identification, the associated pathophysiology, and the promising potential of gene therapy. Ultimately, our objective is to provide a comprehensive and forward-looking perspective on the emerging research arena of NDDs.

Circulating Nucleic Acids in Colorectal Cancer: Diagnostic and Prognostic Value

Colorectal cancer (CRC) is the third most prevalent cancer in the world and the fourth leading cause of cancer-related mortality. DNA (cfDNA/ctDNA) and RNA (cfRNA/ctRNA) in the blood are promising noninvasive biomarkers for molecular profiling, screening, diagnosis, treatment management, and prognosis of CRC. Technological advancements that enable precise detection of both genetic and epigenetic abnormalities, even in minute quantities in circulation, can overcome some of these challenges. This review focuses on testing for circulating nucleic acids in the circulation as a noninvasive method for CRC detection, monitoring, detection of minimal residual disease, and patient management. In addition, the benefits and drawbacks of various diagnostic techniques and associated bioinformatics tools have been detailed.

Mutation profile in liquid biopsy tested by next generation sequencing in Mexican patients with non-small cell lung carcinoma and its impact on survival

Background

Lung cancer represents a significant global health concern, often diagnosed in its advanced stages. The advent of massive DNA sequencing has revolutionized the landscape of cancer treatment by enabling the identification of target mutations and the development of tailored therapeutic approaches. Unfortunately, access to DNA sequencing technology remains limited in many developing countries. In this context, we emphasize the critical importance of integrating this advanced technology into healthcare systems in developing nations to improve treatment outcomes.

Methods

We conducted an analysis of electronic clinical records of patients with confirmed advanced non-small cell lung cancer (NSCLC) and a verified negative status for the epidermal growth factor receptor (EGFR) mutation. These patients underwent next-generation sequencing (NGS) for molecular analysis. We performed descriptive statistical analyses for each variable and conducted both univariate and multivariate statistical analyses to assess their impact on progression-free survival (PFS) and overall survival (OS). Additionally, we classified genetic mutations as actionable or non-actionable based on the European Society for Medical Oncology Scale of Clinical Actionability of Molecular Targets (ESCAT) guidelines.

Results

Our study included a total of 127 patients, revealing the presence of twenty-one distinct mutations. The most prevalent mutations were EGFR (18.9%) and Kirsten rat sarcoma viral oncogene homolog (KRAS) (15.7%). Notably, anaplastic lymphoma kinase (ALK) [hazard ratio (HR): 0.258, P<0.001], tumor mutation burden (TMB) (HR: 2.073, P=0.042) and brain magnetic resonance imaging (MRI) (HR: 0.470, P=0.032) demonstrated statistical significance in both the univariate and multivariate analyses with respect to PFS. In terms of OS, ALK (HR: 0.285, P<0.001) and EGFR (HR: 0.482, P=0.024) exhibited statistical significance in both analyses. Applying the ESCAT classification system, we identified actionable genomic variations (ESCAT level-1), including EGFR, ALK, breast cancer (BRAF) gene, c-ros oncogene 1 (ROS1), and rearranged during transfection (RET) gene, in 32.3% of the patients.

Conclusions

Our findings from massive DNA sequencing underscore that 32.3% of patients who test negative for the EGFR mutation possess other targetable mutations, enabling them to receive personalized, targeted therapies at an earlier stage of their disease. Implementing massive DNA sequencing in developing countries is crucial to enhance survival rates among NSCLC patients and guide more effective treatment strategies.

Retracted: A Comprehensive Review of Performance of Next-Generation Sequencing Platforms

[This retracts the article DOI: 10.1155/2022/3457806.].

DNA Sequencing Technologies and DNA Barcoding

DNA barcodes are short, standardized DNA segments that geneticists can use to identify all living taxa. On the other hand, DNA barcoding identifies species by analyzing these specific regions against a DNA barcode reference library. In its initial years, DNA barcodes sequenced by Sanger's method were extensively used by taxonomists for the characterization and identification of species. But in recent years, DNA barcoding by next-generation sequencing (NGS) has found broader applications, such as quality control, biomonitoring of protected species, and biodiversity assessment. Technological advancements have also paved the way to metabarcoding, which has enabled massive parallel sequ.encing of complex bulk samples using high-throughput sequencing techniques. In future, DNA barcoding along with high-throughput techniques will show stupendous progress in taxonomic classification with reference to available sequence data.

Presence of Extended-Spectrum Beta-Lactamase-Producing Escherichia coli in Food-Producing and Companion Animals and Wildlife on Small-Holder Farms of Floreana Island, Galápagos Islands

Background: Antimicrobial resistance (AR) has led to increasing human and animal morbidity and mortality and negative consequences for the environment. AR among Escherichia coli (EC) is on the rise, with serious concerns about extended-spectrum β-lactamase-producing E. coli (ESBL-EC). In the Galápagos Islands, where antimicrobials are available without a prescription, growing demands for food production can drive antimicrobial use. Food producing animals are at the interface of wildlife and environmental health on the smallest human-inhabited Galápagos Island, Floreana. We sought to determine if ESBL-EC were present in Floreana Island farm animal species and nearby wildlife and the relatedness of ESBL-EC isolates identified. Materials and Methods: During July 4-5, 2022, we visited 8 multispecies farms, representing 75% of food-producing animal production on Floreana, and collected 227 fecal samples from farm animals and wildlife. Each sample was plated on MacConkey agar supplemented with cefotaxime (4 μg/mL). Results: ESBL-EC was isolated from 20 (9%) fecal samples collected from pigs (N = 10), chickens (N = 6), wildlife (N = 3), and dog (N = 1). All ESBL-EC isolates were from samples taken at three (38%) of the eight farms. Fifteen (75%) of the ESBL-EC isolates were from a single farm. All ESBL-EC isolates were multidrug resistant. The most prevalent ESBL genes belonged to the blaCTX-M group. Among the typeable isolates from the farm with the largest proportion of ESBL-EC isolates (N = 14), we observed nine unique pulsed-field gel electrophoresis (PFGE) patterns, with identical patterns present across pig and chicken isolates. PFGE patterns in the three farms with ESBL-EC isolates were different. Conclusions: These results lend support for future routine AR monitoring activities at the livestock-wildlife interface in Galápagos to characterize potential interspecies transmission of AR bacteria and AR genes in this unique protected ecosystem, and the related human, animal, and environmental health impacts, and to formulate interventions to reduce AR spread in this setting.

Is the metabarcoding ripe enough to be applied to the authentication of foodstuff of animal origin? A systematic review

Food authentication using molecular techniques is of great importance to fight food fraud. Metabarcoding, based on the next-generation sequencing (NGS) technologies, allowing large-scale taxonomic identification of complex samples via massive parallel sequencing of fragments (called DNA barcodes) simultaneously, has become increasingly popular in many scientific fields. A systematic review to answer the question "Is the metabarcoding ripe enough to be applied to the authentication of foodstuff of animal origin?" is presented. The inclusion criteria were focused on the selection of scientific papers (SPs) only applying metabarcoding to foodstuff of animal origin collected on the market. The 23 included SPs were first analyzed with respect to the metabarcoding phases: library preparation (target genes, primer pairs, and fragment length), sequencing (NGS platforms), and final data analysis (bioinformatic pipelines). Given the importance of primer selection, the taxonomic coverage of the used primers was also evaluated. In addition, the SPs were scored based on the use of quality control measures (procedural blanks, positive controls, replicates, curated databases, and thresholds to filter the data). A lack of standardized protocols, especially with respect to the target barcode/s and the universal primer/s, and the infrequent application of the quality control measures, leads to answer that metabarcoding is not ripe enough for authenticating foodstuff of animal origin. However, the observed trend of the SP quality improvement over the years is encouraging. Concluding, a proper protocol standardization would allow a wider use of metabarcoding by both official and private laboratories, enabling this method to become the primary for the authentication of foodstuffs of animal origin.

The Genomics in Emerging Marine Systems Checklist for Clear and Reproducible Genomics in Emerging, Marine Systems

Genome sequencing becomes more accessible and powerful every year, but there is a lack of consensus on what information should be provided in publications that include genomic data. The result is a flood of sequencing data without a framework to evaluate its quality and completeness, hindering reproducibility. In non-model taxa in marine systems, a lack of detail in methods sections often hinders future researchers from adopting improved techniques, leaving them to repeat costly protocols and take up computational (wall) time with programs that are already known to fail. Here, I present a set of guidelines tailored for marine taxa (emerging model organisms) to promote consistency between publications, increase transparency of sequencing projects, and preserve the value of sequence data as sequencing technologies advance. Included is a checklist to (1) guide authors toward including more detailed information in their manuscripts, (2) expand data availability, and (3) assist reviewers to thoroughly vet methods and results of future 'omic publications. This set of guidelines will support the usefulness of 'omic data in future analyses by providing a framework to document and evaluate these data, leading to transparent and reproducible genomics research on emerging marine systems.

Genetic basis and origin of resistance to acetolactate synthase inhibitors in Amaranthus palmeri from Spain and Italy

BACKGROUND

Amaranthus palmeri is an aggressive annual weed native to the United States, which has become invasive in some European countries. Populations resistant to acetolactate synthase (ALS) inhibitors have been recorded in Spain and Italy, but the evolutionary origin of the resistance traits remains unknown. Bioassays were conducted to identify cross-resistance to ALS inhibitors and a haplotype-based genetic approach was used to elucidate the origin and distribution of resistance in both countries.

RESULTS

Amaranthus palmeri populations were resistant to thifensulfuron-methyl and imazamox, and the 574-Leu mutant ALS allele was found to be the main cause of resistance among them. In two Spanish populations, 376-Glu and 197-Thr mutant ALS alleles were also found. The haplotype analyses revealed the presence of two and four distinct 574-Leu mutant haplotypes in the Italian and Spanish populations, respectively. None was common to both countries, but some mutant haplotypes were shared between geographically close populations or between populations more than 100 km apart. Wide genetic diversity was found in two very close Spanish populations.

CONCLUSION

ALS-resistant A. palmeri populations were introduced to Italy and Spain from outside Europe. Populations from both countries have different evolutionary histories and originate from independent introduction events. ALS resistance then spread over short and long distances by seed dispersal. The higher number and genetic diversity among mutant haplotypes from the Spanish populations indicated recurrent invasions. The implementation of control tactics to limit seed dispersal and the establishment of A. palmeri is recommended in both countries. © 2023 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Microbial cell-free DNA detection: Minimally invasive diagnosis of infectious diseases

BACKGROUND

Detection of infectious diseases, especially among immunocompromised and patients on prolonged anti-microbial treatment, remains challenging, limited by conventional techniques with low sensitivity and long-turnaround time. Molecular detection by polymerase chain reaction (PCR) also has limited utility as it requires a targeted approach with prior suspicion of the infecting organism. Advancements in sequencing methodologies, specifically next-generation sequencing (NGS), have presented a promising opportunity to identify pathogens in cases where conventional techniques may be inadequate. However, the direct application of these techniques for diagnosing invasive infections is still limited by the need for invasive sampling, highlighting the pressing need to develop and implement non-invasive or minimally invasive approaches to improve the diagnosis of invasive infections.

OBJECTIVES

The objectives of this article are to explore the notable features, clinical utility, and constraints associated with the detection of microbial circulating cell-free DNA (mcfDNA) as a minimally invasive diagnostic tool for infectious diseases.

CONTENT

The mcfDNA detection provides an opportunity to identify micro-organisms in the blood of a patient. It is especially beneficial in immunocompromised patients where invasive sampling is not possible or where repeated cultures are negative. This review will discuss the applications and constraints of detecting mcfDNA for diagnosing infections and the various platforms available for its detection.

O’Brien T, Perucca P, Ge Z, Anderson A. Applications for Deep Learning in Epilepsy Genetic Research

Epilepsy is a group of brain disorders characterised by an enduring predisposition to generate unprovoked seizures. Fuelled by advances in sequencing technologies and computational approaches, more than 900 genes have now been implicated in epilepsy. The development and optimisation of tools and methods for analysing the vast quantity of genomic data is a rapidly evolving area of research. Deep learning (DL) is a subset of machine learning (ML) that brings opportunity for novel investigative strategies that can be harnessed to gain new insights into the genomic risk of people with epilepsy. DL is being harnessed to address limitations in accuracy of long-read sequencing technologies, which improve on short-read methods. Tools that predict the functional consequence of genetic variation can represent breaking ground in addressing critical knowledge gaps, while methods that integrate independent but complimentary data enhance the predictive power of genetic data. We provide an overview of these DL tools and discuss how they may be applied to the analysis of genetic data for epilepsy research.

Why is there no service to support taxonomy?

Increasing complexity and specialisation of modern sciences has led to increasingly collaborative publications, as well as the involvement of commercial services. Modern integrative taxonomy likewise depends on many lines of evidence and is increasingly complex, but the trend of collaboration lags and various attempts at 'turbo taxonomy' have been unsatisfactory. We are developing a taxonomic service in the Senckenberg Ocean Species Alliance to provide fundamental data for new species descriptions. This will also function as a hub to connect a global network of taxonomists, assembling an alliance of scientists working on potential new species to tackle both the extinction and inclusion crises we face today. The current rate of new species descriptions is simply too slow; the discipline is often dismissed as old fashioned, and there is a crisis level need for taxonomic descriptions to come to grips with the scale of Anthropocene biodiversity loss. Here, we envision how the process of describing and naming species would benefit from a service supporting the acquisition of descriptive data. Also see the video abstract here: https://youtu.be/E8q3KJor_F8.

Fungal taxonomy: A puzzle with many missing pieces

Fungi are multifaceted organisms found in almost all ecosystems on Earth, where they establish various types of symbiosis with other living beings. Despite being recognized by humans since ancient times, and the high number of works delving into their biology and ecology, much is still unknown about these organisms. Some criteria classically used for their study are nowadays limited, generating confusion in categorizing them, and even more, when trying to understand their genealogical relationships. To identify species within Fungi, phenotypic characters to date are not sufficient, and to construct a broad phylogeny or a phylogeny of a particular group, there are still gaps affecting the generated trees, making them unstable and easily debated. For health professionals, fungal identification at lower levels such as genus and species, is enough to select the most appropriate therapy for their control, understand the epidemiology of clinical pictures associated, and recognize outbreaks and antimicrobial resistance. However, the taxonomic location within the kingdom, information with apparently little relevance, can allow phylogenetic relationships to be established between fungal taxa, facilitating the understanding of their biology, distribution in nature, and pathogenic potential evolution. Advances in molecular biology and computer science techniques from the last 30 years have led to crucial changes aiming to establish the criteria to define a fungal species, allowing us to reach a kind of stable phylogenetic construction. However, there is still a long way to go, and it requires the joint work of the scientific community at a global level and support for basic research.

Complete chloroplast genome sequence of Rhododendronmariesii and comparative genomics of related species in the family Ericaeae

Rhododendronmariesii Hemsley et Wilson, 1907, a typical member of the family Ericaeae, possesses valuable medicinal and horticultural properties. In this research, the complete chloroplast (cp) genome of R.mariesii was sequenced and assembled, which proved to be a typical quadripartite structure with the length of 203,480 bp. In particular, the lengths of the large single copy region (LSC), small single copy region (SSC), and inverted repeat regions (IR) were 113,715 bp, 7,953 bp, and 40,918 bp, respectively. Among the 151 unique genes, 98 were protein-coding genes, 8 were tRNA genes, and 45 were rRNA genes. The structural characteristics of the R.mariesiicp genome was similar to other angiosperms. Leucine was the most representative amino acid, while cysteine was the lowest representative. Totally, 30 codons showed obvious codon usage bias, and most were A/U-ending codons. Six highly variable regions were observed, such as trnK-pafI and atpE-rpoB, which could serve as potential markers for future barcoding and phylogenetic research of R.mariesii species. Coding regions were more conserved than non-coding regions. Expansion and contraction in the IR region might be the main length variation in R.mariesii and related Ericaeae species. Maximum-likelihood (ML) phylogenetic analysis revealed that R.mariesii was relatively closed to the R.simsii Planchon, 1853 and R.pulchrum Sweet,1831. This research will supply rich genetic resource for R.mariesii and related species of the Ericaeae.

A chromosome-scale and haplotype-resolved genome assembly of carnation (Dianthus caryophyllus) based on high-fidelity sequencing

Dianthus caryophyllus is an economic species often considered excellent cut flowers and is suitable for bouquets and gardens. Here, we assembled the haplotype-resolved genome of D. caryophyllus 'Aili' at the chromosome level for the first time. The total lengths of the two assembled haplotypes of carnation were 584.88 Mb for haplotype genome 1 (hap1) and 578.78 Mb for haplotype genome 2 (hap2), respectively. We predicted a total of 44,098 and 42,425 protein-coding genes, respectively. The remarkable structure variation was identified between two haplotypes. Moreover, we identified 403.80 Mb of transposable elements (TEs) in hap1, which accounted for 69.34% of the genome. In contrast, hap2 had 402.70 Mb of TEs, representing 69.61% of the genome. Long terminal repeats were the predominant transposable elements. Phylogenetic analysis showed that the species differentiation time between carnation and gypsophila was estimated to be ~54.43 MYA. The unique gene families of carnation genomes were identified in 'Aili' and previously published 'Francesco' and 'Scarlet Queen'. The assembled and annotated haplotype-resolved D. caryophyllus genome not only promises to facilitate molecular biology studies but also contributes to genome-level evolutionary studies.

Characterization of a strain-specific CD-1 reference genome reveals potential inter- and intra-strain functional variability

BACKGROUND

CD-1 is an outbred mouse stock that is frequently used in toxicology, pharmacology, and fundamental biomedical research. Although inbred strains are typically better suited for such studies due to minimal genetic variability, outbred stocks confer practical advantages over inbred strains, such as improved breeding performance and low cost. Knowledge of the full genetic variability of CD-1 would make it more useful in toxicology, pharmacology, and fundamental biomedical research.

RESULTS

We performed deep genomic DNA sequencing of CD-1 mice and used the data to identify genome-wide SNPs, indels, and germline transposable elements relative to the mm10 reference genome. We used multiple genome-wide sequencing data types and previously published CD-1 SNPs to validate our called variants. We used the called variants to construct a strain-specific CD-1 reference genome, which we show can improve mappability and reduce experimental biases from genome-wide sequencing data derived from CD-1 mice. Based on previously published ChIP-seq and ATAC-seq data, we find evidence that genetic variation between CD-1 mice can lead to alterations in transcription factor binding. We also identified a number of variants in the coding region of genes which could have effects on translation of genes.

CONCLUSIONS

We have identified millions of previously unidentified CD-1 variants with the potential to confound studies involving CD-1. We used the identified variants to construct a CD-1-specific reference genome, which can improve accuracy and reduce bias when aligning genomics data derived from CD-1 mice.

Nanopore sequencing technology and its applications

Since the development of Sanger sequencing in 1977, sequencing technology has played a pivotal role in molecular biology research by enabling the interpretation of biological genetic codes. Today, nanopore sequencing is one of the leading third-generation sequencing technologies. With its long reads, portability, and low cost, nanopore sequencing is widely used in various scientific fields including epidemic prevention and control, disease diagnosis, and animal and plant breeding. Despite initial concerns about high error rates, continuous innovation in sequencing platforms and algorithm analysis technology has effectively addressed its accuracy. During the coronavirus disease (COVID-19) pandemic, nanopore sequencing played a critical role in detecting the severe acute respiratory syndrome coronavirus-2 virus genome and containing the pandemic. However, a lack of understanding of this technology may limit its popularization and application. Nanopore sequencing is poised to become the mainstream choice for preventing and controlling COVID-19 and future epidemics while creating value in other fields such as oncology and botany. This work introduces the contributions of nanopore sequencing during the COVID-19 pandemic to promote public understanding and its use in emerging outbreaks worldwide. We discuss its application in microbial detection, cancer genomes, and plant genomes and summarize strategies to improve its accuracy.

Next-Generation Sequencing Technology: Current Trends and Advancements

The advent of next-generation sequencing (NGS) has brought about a paradigm shift in genomics research, offering unparalleled capabilities for analyzing DNA and RNA molecules in a high-throughput and cost-effective manner. This transformative technology has swiftly propelled genomics advancements across diverse domains. NGS allows for the rapid sequencing of millions of DNA fragments simultaneously, providing comprehensive insights into genome structure, genetic variations, gene expression profiles, and epigenetic modifications. The versatility of NGS platforms has expanded the scope of genomics research, facilitating studies on rare genetic diseases, cancer genomics, microbiome analysis, infectious diseases, and population genetics. Moreover, NGS has enabled the development of targeted therapies, precision medicine approaches, and improved diagnostic methods. This review provides an insightful overview of the current trends and recent advancements in NGS technology, highlighting its potential impact on diverse areas of genomic research. Moreover, the review delves into the challenges encountered and future directions of NGS technology, including endeavors to enhance the accuracy and sensitivity of sequencing data, the development of novel algorithms for data analysis, and the pursuit of more efficient, scalable, and cost-effective solutions that lie ahead.

Artefact Profiling: Panomics Approaches for Understanding the Materiality of Written Artefacts

This review explains the strategies behind genomics, proteomics, metabolomics, metallomics and isotopolomics approaches and their applicability to written artefacts. The respective sub-chapters give an insight into the analytical procedure and the conclusions drawn from such analyses. A distinction is made between information that can be obtained from the materials used in the respective manuscript and meta-information that cannot be obtained from the manuscript itself, but from residues of organisms such as bacteria or the authors and readers. In addition, various sampling techniques are discussed in particular, which pose a special challenge in manuscripts. The focus is on high-resolution, non-targeted strategies that can be used to extract the maximum amount of information about ancient objects. The combination of the various omics disciplines (panomics) especially offers potential added value in terms of the best possible interpretations of the data received. The information obtained can be used to understand the production of ancient artefacts, to gain impressions of former living conditions, to prove their authenticity, to assess whether there is a toxic hazard in handling the manuscripts, and to be able to determine appropriate measures for their conservation and restoration.

Diagnosis of invasive fungal infections: challenges and recent developments

BACKGROUND

The global burden of invasive fungal infections (IFIs) has shown an upsurge in recent years due to the higher load of immunocompromised patients suffering from various diseases. The role of early and accurate diagnosis in the aggressive containment of the fungal infection at the initial stages becomes crucial thus, preventing the development of a life-threatening situation. With the changing demands of clinical mycology, the field of fungal diagnostics has evolved and come a long way from traditional methods of microscopy and culturing to more advanced non-culture-based tools. With the advent of more powerful approaches such as novel PCR assays, T2 Candida, microfluidic chip technology, next generation sequencing, new generation biosensors, nanotechnology-based tools, artificial intelligence-based models, the face of fungal diagnostics is constantly changing for the better. All these advances have been reviewed here giving the latest update to our readers in the most orderly flow.

MAIN TEXT

A detailed literature survey was conducted by the team followed by data collection, pertinent data extraction, in-depth analysis, and composing the various sub-sections and the final review. The review is unique in its kind as it discusses the advances in molecular methods; advances in serology-based methods; advances in biosensor technology; and advances in machine learning-based models, all under one roof. To the best of our knowledge, there has been no review covering all of these fields (especially biosensor technology and machine learning using artificial intelligence) with relevance to invasive fungal infections.

CONCLUSION

The review will undoubtedly assist in updating the scientific community's understanding of the most recent advancements that are on the horizon and that may be implemented as adjuncts to the traditional diagnostic algorithms.

The Landscape of the DNA Transposons in the Genome of the Horezu_LaPeri Strain of Drosophila melanogaster

Natural transposons (NTs) represent mobile DNA sequences found in both prokaryotic and eukaryotic genomes. Drosophila melanogaster (the fruit fly) is a eukaryotic model organism with NTs standing for about 20% of its genome and has contributed significantly to the understanding of various aspects of transposon biology. Our study describes an accurate approach designed to map class II transposons (DNA transposons) in the genome of the Horezu_LaPeri fruit fly strain, consecutive to Oxford Nanopore Technology sequencing. A whole genome bioinformatics analysis was conducted using Genome ARTIST_v2, LoRTE and RepeatMasker tools to identify DNA transposons insertions. Then, a gene ontology enrichment analysis was performed in order to evaluate the potential adaptive role of some DNA transposons insertions. Herein, we describe DNA transposon insertions specific for the Horezu_LaPeri genome and a predictive functional analysis of some insertional alleles. The PCR validation of P-element insertions specific for this fruit fly strain, along with a putative consensus sequence for the KP element, is also reported. Overall, the genome of the Horezu_LaPeri strain contains several insertions of DNA transposons associated with genes known to be involved in adaptive processes. For some of these genes, insertional alleles obtained via mobilization of the artificial transposons were previously reported. This is a very alluring aspect, as it suggests that insertional mutagenesis experiments conducting adaptive predictions for laboratory strains may be confirmed by mirroring insertions which are expected to be found at least in some natural fruit fly strains.

Narrative Review: Update on the Molecular Diagnosis of Fragile X Syndrome

The diagnosis and management of fragile X syndrome (FXS) have significantly improved in the last three decades, although the current diagnostic techniques are not yet able to precisely identify the number of repeats, methylation status, level of mosaicism, and/or the presence of AGG interruptions. A high number of repeats (>200) in the fragile X messenger ribonucleoprotein 1 gene (FMR1) results in hypermethylation of promoter and gene silencing. The actual molecular diagnosis is performed using a Southern blot, TP-PCR (Triplet-Repeat PCR), MS-PCR (Methylation-Specific PCR), and MS-MLPA (Methylation-Specific MLPA) with some limitations, with multiple assays being necessary to completely characterise a patient with FXS. The actual gold standard diagnosis uses Southern blot; however, it cannot accurately characterise all cases. Optical genome mapping is a new technology that has also been developed to approach the diagnosis of fragile X syndrome. Long-range sequencing represented by PacBio and Oxford Nanopore has the potential to replace the actual diagnosis and offers a complete characterization of molecular profiles in a single test. The new technologies have improved the diagnosis of fragile X syndrome and revealed unknown aberrations, but they are a long way from being used routinely in clinical practice.

Phenanthrene Degradation by Photosynthetic Bacterial Consortium Dominated by Fischerella sp

Microbial degradation of aromatic hydrocarbons is an emerging technology, and it is well recognized for its economic methods, efficiency, and safety; however, its exploration is still scarce and greater emphasis on cyanobacteria-bacterial mutualistic interactions is needed. We evaluated and characterized the phenanthrene biodegradation capacity of consortium dominated by Fischerella sp. under holoxenic conditions with aerobic heterotrophic bacteria and their molecular identification through 16S rRNA Illumina sequencing. Results indicated that our microbial consortium can degrade up to 92% of phenanthrene in five days. Bioinformatic analyses revealed that consortium was dominated by Fischerella sp., however different members of Nostocaceae and Weeksellaceae, as well as several other bacteria, such as Chryseobacterium, and Porphyrobacter, were found to be putatively involved in the biological degradation of phenanthrene. This work contributes to a better understanding of biodegradation of phenanthrene by cyanobacteria and identify the microbial diversity related.

Application of Targeted Next-Generation Sequencing for the Investigation of Thalassemia in a Developing Country: A Single Center Experience

Thalassemia is identified as a prevalent disease in Malaysia, known to be one of the developing countries. Fourteen patients with confirmed cases of thalassemia were recruited from the Hematology Laboratory. The molecular genotypes of these patients were tested using the multiplex-ARMS and GAP-PCR methods. The samples were repeatedly investigated using the Devyser Thalassemia kit (Devyser, Sweden), a targeted NGS panel targeting the coding regions of hemoglobin genes, namely the HBA1, HBA2, and HBB genes, which were used in this study. There were many different genetic variants found in 14 unrelated cases. Out of all fourteen cases, NGS was able to determine an additional -50 G>A (HBB:c.-100G>A) that were not identified by the multiplex-ARMS method, including HBA2 mutations, namely CD 79 (HBA2:c.239C>G). Other than that, CD 142 (HBA2:c.427T>C) and another non-deletional alpha thalassemia and alpha triplication were also not picked up by the GAP-PCR methods. We illustrated a broad, targeted NGS-based test that proposes benefits rather than using traditional screening or basic molecular methods. The results of this study should be heeded, as this is the first report on the practicality of targeted NGS concerning the biological and phenotypic features of thalassemia, especially in a developing population. Discovering rare pathogenic thalassemia variants and additional secondary modifiers may facilitate precise diagnosis and better disease prevention.

Complete Chloroplast Genome of Four Thai Native Dioscorea Species: Structural, Comparative and Phylogenetic Analyses

The chloroplast genomes of Dioscorea brevipetiolata, D. depauperata, D. glabra, and D. pyrifolia are 153,370–153,503 bp in size. A total of 113 genes were predicted, including 79 protein-coding sequences (CDS), 30 tRNA, and four rRNA genes. The overall GC content for all four species was 37%. Only mono-, di-, and trinucleotides were present in the genome. Genes adjacent to the junction borders were similar in all species analyzed. Eight distinct indel variations were detected in the chloroplast genome alignment of 24 Dioscorea species. At a cut-off point of Pi = 0.03, a sliding window analysis based on 25 chloroplast genome sequences of Dioscorea species revealed three highly variable regions, which included three CDS (trnC, ycf1, and rpl32), as well as an intergenic spacer region, ndhF-rpl32. A phylogenetic tree based on the complete chloroplast genome sequence displayed an almost fully resolved relationship in Dioscorea. However, D. brevipetiolata, D. depauperata, and D. glabra were clustered together with D. alata, while D. pyrifolia was closely related to D. aspersa. As Dioscorea is a diverse genus, genome data generated in this study may contribute to a better understanding of the genetic identity of these species, which would be useful for future taxonomic work of Dioscorea.

Molecular Detection and Identification of Plant-Associated Lactiplantibacillus plantarum

Lactiplantibacillus plantarum is a lactic acid bacterium often isolated from a wide variety of niches. Its ubiquity can be explained by a large, flexible genome that helps it adapt to different habitats. The consequence of this is great strain diversity, which may make their identification difficult. Accordingly, this review provides an overview of molecular techniques, both culture-dependent, and culture-independent, currently used to detect and identify L. plantarum. Some of the techniques described can also be applied to the analysis of other lactic acid bacteria.

Design and Validation of a Custom Next-Generation Sequencing Panel in Pediatric Acute Lymphoblastic Leukemia

The molecular landscape of acute lymphoblastic leukemia (ALL) is highly heterogeneous, and genetic lesions are clinically relevant for diagnosis, risk stratification, and treatment guidance. Next-generation sequencing (NGS) has become an essential tool for clinical laboratories, where disease-targeted panels are able to capture the most relevant alterations in a cost-effective and fast way. However, comprehensive ALL panels assessing all relevant alterations are scarce. Here, we design and validate an NGS panel including single-nucleotide variants (SNVs), insertion-deletions (indels), copy number variations (CNVs), fusions, and gene expression (ALLseq). ALLseq sequencing metrics were acceptable for clinical use and showed 100% sensitivity and specificity for virtually all types of alterations. The limit of detection was established at a 2% variant allele frequency for SNVs and indels, and at a 0.5 copy number ratio for CNVs. Overall, ALLseq is able to provide clinically relevant information to more than 83% of pediatric patients, making it an attractive tool for the molecular characterization of ALL in clinical settings.

Translational Bioinformatics Applied to the Study of Complex Diseases

Translational Bioinformatics (TBI) is defined as the union of translational medicine and bioinformatics. It emerges as a major advance in science and technology by covering everything, from the most basic database discoveries, to the development of algorithms for molecular and cellular analysis, as well as their clinical applications. This technology makes it possible to access the knowledge of scientific evidence and apply it to clinical practice. This manuscript aims to highlight the role of TBI in the study of complex diseases, as well as its application to the understanding and treatment of cancer. An integrative literature review was carried out, obtaining articles through several websites, among them: PUBMED, Science Direct, NCBI-PMC, Scientific Electronic Library Online (SciELO), and Google Academic, published in English, Spanish, and Portuguese, indexed in the referred databases and answering the following guiding question: "How does TBI provide a scientific understanding of complex diseases?" An additional effort is aimed at the dissemination, inclusion, and perpetuation of TBI knowledge from the academic environment to society, helping the study, understanding, and elucidating of complex disease mechanics and their treatment.

Applying multi-omics toward tumor microbiome research

Rather than a "short-term tenant," the tumor microbiome has been shown to play a vital role as a "permanent resident," affecting carcinogenesis, cancer development, metastasis, and cancer therapies. As the tumor microbiome has great potential to become a target for the early diagnosis and treatment of cancer, recent research on the relevance of the tumor microbiota has attracted a wide range of attention from various scientific fields, resulting in remarkable progress that benefits from the development of interdisciplinary technologies. However, there are still a great variety of challenges in this emerging area, such as the low biomass of intratumoral bacteria and unculturable character of some microbial species. Due to the complexity of tumor microbiome research (e.g., the heterogeneity of tumor microenvironment), new methods with high spatial and temporal resolution are urgently needed. Among these developing methods, multi-omics technologies (combinations of genomics, transcriptomics, proteomics, and metabolomics) are powerful approaches that can facilitate the understanding of the tumor microbiome on different levels of the central dogma. Therefore, multi-omics (especially single-cell omics) will make enormous impacts on the future studies of the interplay between microbes and tumor microenvironment. In this review, we have systematically summarized the advances in multi-omics and their existing and potential applications in tumor microbiome research, thus providing an omics toolbox for investigators to reference in the future.

Analysis of the Toll and Spaetzle Genes Involved in Toll Pathway-Dependent Antimicrobial Gene Induction in the Red Flour Beetle, Tribolium castaneum (Coleoptera; Tenebrionidae)

Insects rely only on their innate immune system to protect themselves from pathogens. Antimicrobial peptide (AMP) production is the main immune reaction in insects. In Drosophila melanogaster, the reaction is regulated mainly by the Toll and immune deficiency (IMD) pathways. Spaetzle proteins, activated by immune signals from upstream components, bind to Toll proteins, thus, activating the Toll pathway, which in turn, induces AMP genes. Previous studies have shown the difference in immune systems related to Toll and IMD pathways between D. melanogaster and Tribolium castaneum. In T. castaneum, nine Toll and seven spaetzle (spz) genes were identified. To extend our understanding of AMP production by T. castaneum, we conducted functional assays of Toll and spaetzle genes related to Toll-pathway-dependent AMP gene expression in T. castaneum under challenge with bacteria or budding yeast. The results revealed that Toll3 and Toll4 double-knockdown and spz7 knockdown strongly and moderately reduced the Toll-pathway-dependent expression of AMP genes, respectively. Moreover, Toll3 and Toll4 double-knockdown pupae more rapidly succumbed to entomopathogenic bacteria than the control pupae, but spz7 knockdown pupae did not. The results suggest that Toll3 and Toll4 play a large role in Toll-pathway-dependent immune reactions, whereas spz7 plays a small part.

Czy plastik może rozpocząć nową erę w archiwizacji danych?

With the rapid development of information technology, many aspects of our lives are undergoing a digital transformation. An increasing number of users are going online every year, and constantly improving artificial intelligence is gaining popularity, which leads to the growing production of information. Nowadays, information is usually stored in data centres, which will be forced to increase their space with the constant flow of new bits of information. Together with the increase in their space, energy consumption and associated maintenance costs are escalating. In 2021, global data centre power consumption was 220–320 TWh, which is about 0.9–1.3% of global power consumption. Continuous power supply for database operations is responsible for about 1% of total carbon dioxide emissions. Furthermore, it has already been reported that with the exponentially growing amount of data, in about 20 years, the amount of silicon for microprocessors will no longer be sufficient to store all the information. Therefore, scientists are looking for alternatives to the currently used data storage solutions and are developing new technologies using chemical molecules. Recently, even plastic has been explored as a data carrier. In this work, we present examples of new technologies for data storage in polymers. We have discussed polymers as data carriers in comparison with currently used solutions and deliberated whether plastic can become a future material for information archiving.