Advances in computational and experimental approaches for deciphering transcriptional regulatory networks: Understanding the roles of cis-regulatory elements is essential, and recent research utilizing MPRAs, STARR-seq, CRISPR-Cas9, and machine learning has yielded valuable insights.

Understanding the influence of cis-regulatory elements on gene regulation poses numerous challenges given complexities stemming from variations in transcription factor (TF) binding, chromatin accessibility, structural constraints, and cell-type differences. This review discusses the role of gene regulatory networks in enhancing understanding of transcriptional regulation and covers construction methods ranging from expression-based approaches to supervised machine learning. Additionally, key experimental methods, including MPRAs and CRISPR-Cas9-based screening, which have significantly contributed to understanding TF binding preferences and cis-regulatory element functions, are explored. Lastly, the potential of machine learning and artificial intelligence to unravel cis-regulatory logic is analyzed. These computational advances have far-reaching implications for precision medicine, therapeutic target discovery, and the study of genetic variations in health and disease.

Massively parallel reporter assays and mouse transgenic assays provide complementary information about neuronal enhancer activity.

Genetic studies find hundreds of thousands of noncoding variants associated with psychiatric disorders. Massively parallel reporter assays (MPRAs) and in vivo transgenic mouse assays can be used to assay the impact of these variants. However, the relevance of MPRAs to in vivo function is unknown and transgenic assays suffer from low throughput. Here, we studied the utility of combining the two assays to study the impact of non-coding variants. We carried out an MPRA on over 50,000 sequences derived from enhancers validated in transgenic mouse assays and from multiple fetal neuronal ATAC-seq datasets. We also tested over 20,000 variants, including synthetic mutations in highly active neuronal enhancers and 177 common variants associated with psychiatric disorders. Variants with a high impact on MPRA activity were further tested in mice. We found a strong and specific correlation between MPRA and mouse neuronal enhancer activity including changes in neuronal enhancer activity in mouse embryos for variants with strong MPRA effects. Mouse assays also revealed pleiotropic variant effects that could not be observed in MPRA. Our work provides a large catalog of functional neuronal enhancers and variant effects and highlights the effectiveness of combining MPRAs and mouse transgenic assays.

kmerDB: A database encompassing the set of genomic and proteomic sequence information for each species.

The decrease in sequencing expenses has facilitated the creation of reference genomes and proteomes for an expanding array of organisms. Nevertheless, no established repository that details organism-specific genomic and proteomic sequences of specific lengths, referred to as kmers, exists to our knowledge. In this article, we present kmerDB, a database accessible through an interactive web interface that provides kmer-based information from genomic and proteomic sequences in a systematic way. kmerDB currently contains 202,340,859,107 base pairs and 19,304,903,356 amino acids, spanning 54,039 and 21,865 reference genomes and proteomes, respectively, as well as 6,905,362 and 149,305,183 genomic and proteomic species-specific sequences, termed quasi-primes. Additionally, we provide access to 5,186,757 nucleic and 214,904,089 peptide sequences absent from every genome and proteome, termed primes. kmerDB features a user-friendly interface offering various search options and filters for easy parsing and searching. The service is available at: www.kmerdb.com.

Visualizing metagenomic and metatranscriptomic data: A comprehensive review.

The fields of Metagenomics and Metatranscriptomics involve the examination of complete nucleotide sequences, gene identification, and analysis of potential biological functions within diverse organisms or environmental samples. Despite the vast opportunities for discovery in metagenomics, the sheer volume and complexity of sequence data often present challenges in processing analysis and visualization. This article highlights the critical role of advanced visualization tools in enabling effective exploration, querying, and analysis of these complex datasets. Emphasizing the importance of accessibility, the article categorizes various visualizers based on their intended applications and highlights their utility in empowering bioinformaticians and non-bioinformaticians to interpret and derive insights from meta-omics data effectively.

The determinants of the rarity of nucleic and peptide short sequences in nature.

The prevalence of nucleic and peptide short sequences across organismal genomes and proteomes has not been thoroughly investigated. We examined 45 785 reference genomes and 21 871 reference proteomes, spanning archaea, bacteria, eukaryotes and viruses to calculate the rarity of short sequences in them. To capture this, we developed a metric of the rarity of each sequence in nature, the rarity index. We find that the frequency of certain dipeptides in rare oligopeptide sequences is hundreds of times lower than expected, which is not the case for any dinucleotides. We also generate predictive regression models that infer the rarity of nucleic and proteomic sequences across nature or within each domain of life and viruses separately. When examining each of the three domains of life and viruses separately, the R² performance of the model predicting rarity for 5-mer peptides from mono- and dipeptides ranged between 0.814 and 0.932. A separate model predicting rarity for 10-mer oligonucleotides from mono- and dinucleotides achieved R² performance between 0.408 and 0.606. Our results indicate that the mono- and dinucleotide composition of nucleic sequences and the mono- and dipeptide composition of peptide sequences can explain a significant proportion of the variance in their frequencies in nature.

Approaches of dengue control: vaccine strategies and future aspects.

Dengue, caused by the dengue virus (DENV), affects millions of people worldwide every year. This virus has two distinct life cycles, one in the human and another in the mosquito, and both cycles are crucial to be controlled. To control the vector of DENV, the mosquito Aedes aegypti, scientists employed many techniques, which were later proved ineffective and harmful in many ways. Consequently, the attention shifted to the development of a vaccine; researchers have targeted the E protein, a surface protein of the virus and the NS1 protein, an extracellular protein. There are several types of vaccines developed so far, such as live attenuated vaccines, recombinant subunit vaccines, inactivated virus vaccines, viral vectored vaccines, DNA vaccines, and mRNA vaccines. Along with these, scientists are exploring new strategies of developing improved version of the vaccine by employing recombinant DNA plasmid against NS1 and also aiming to prevent the infection by blocking the DENV life cycle inside the mosquitoes. Here, we discussed the aspects of research in the field of vaccines until now and identified some prospects for future vaccine developments.

Utilizing nullomers in cell-free RNA for early cancer detection.

Early detection of cancer can significantly improve patient outcomes; however, sensitive and highly specific biomarkers for cancer detection are currently missing. Nullomers are the shortest sequences that are absent from the human genome but can emerge due to somatic mutations in cancer. We examine over 10,000 whole exome sequencing matched tumor-normal samples to characterize nullomer emergence across exonic regions of the genome. We also identify nullomer emerging mutational hotspots within tumor genes. Finally, we provide evidence for the identification of nullomers in cell-free RNA from peripheral blood samples, enabling detection of multiple tumor types. We show multiple tumor classification models with an AUC greater than 0.9, including a hepatocellular carcinoma classifier with an AUC greater than 0.99.

Integrative single-cell characterization of a frugivorous and an insectivorous bat kidney and pancreas.

Frugivory evolved multiple times in mammals, including bats. However, the cellular and molecular components driving it remain largely unknown. Here, we use integrative single-cell sequencing (scRNA-seq and scATAC-seq) on insectivorous (Eptesicus fuscus; big brown bat) and frugivorous (Artibeus jamaicensis; Jamaican fruit bat) bat kidneys and pancreases and identify key cell population, gene expression and regulatory differences associated with the Jamaican fruit bat that also relate to human disease, particularly diabetes. We find a decrease in loop of Henle and an increase in collecting duct cells, and differentially active genes and regulatory elements involved in fluid and electrolyte balance in the Jamaican fruit bat kidney. The Jamaican fruit bat pancreas shows an increase in endocrine and a decrease in exocrine cells, and differences in genes and regulatory elements involved in insulin regulation. We also find that these frugivorous bats share several molecular characteristics with human diabetes. Combined, our work provides insights from a frugivorous mammal that could be leveraged for therapeutic purposes.

Peptide absent sequences emerging in human cancers.

Early diagnosis of cancer can significantly improve survival of cancer patients; however sensitive and highly specific biomarkers for cancer detection are currently lacking for most cancer types. Nullpeptides are short peptides that are absent from the human proteome. Here, we examined the emergence of nullpeptides during cancer development. We analyzed 3,600,964 somatic mutations across 10,064 whole exome sequencing tumor samples spanning 32 cancer types. We analyze RNA-seq data from primary tumor samples to identify the subset of nullpeptides that emerge in highly expresed genes. We show that nullpeptides, and particularly the subset that is highly recurrent across cancer patients, can be identified in tumor biopsy samples. We find that cancer genes show an excess of nullpeptides and detect nullpeptide hotspots in specific loci of oncogenes and tumor suppressors. We also observe that recurrent nullpeptides are more likely to be found in neoantigens, which have been shown to be effective targets for immunotherapy, suggesting that they can be used to prioritize candidates. Our findings provide evidence for the utility of nullpeptides as cancer detection and therapeutic biomarkers.

Transcriptomic profiling of the response to excess iodide in Keap1 hypomorphic mice reveals new gene-environment interactions in thyroid homeostasis.

Iodide plays a pivotal role in thyroid homeostasis due to its crucial involvement in thyroid hormone biosynthesis. Exposure to pharmacological doses of iodide elicits in the thyroid an autoregulatory response to preserve thyroid function, as well as an antioxidant response that is mediated by the Keap1/Nrf2 signaling pathway. The objective of the present study was to investigate the transcriptional response of the thyroid to excess iodide in a background of enhanced Nrf2 signaling. Keap1 knockdown (Keap1KD) mice that have activated Nrf2 signaling were exposed or not to excess iodide in their drinking water for seven days and compared to respective wild-type mice. RNA-sequencing of individual mouse thyroids identified distinct transcriptomic patterns in response to iodide, with Keap1KD mice showing an attenuated inflammatory response, altered thyroidal autoregulation, and enhanced cell growth/proliferative signaling, as confirmed also by Western blotting for key proteins involved in antioxidant, autoregulatory and proliferative responses. These findings underscore novel gene-environment interactions between the activation status of the Keap1/Nrf2 antioxidant response system and the dietary iodide intake, which may have implications not only for the goiter phenotype of Keap1KD mice but also for humans harboring genetic variations in KEAP1 or NFE2L2 or treated with Nrf2-modulating drugs.

The chemotherapeutic drug CX-5461 is a potent mutagen in cultured human cells.

The chemotherapeutic agent CX-5461, or pidnarulex, has been fast-tracked by the United States Food and Drug Administration for early-stage clinical studies of BRCA1-, BRCA2- and PALB2-mutated cancers. It is under investigation in phase I and II trials. Here, we find that, although CX-5461 exhibits synthetic lethality in BRCA1-/BRCA2-deficient cells, it also causes extensive, nonselective, collateral mutagenesis in all three cell lines tested, to magnitudes that exceed known environmental carcinogens.

Frequentmers - a novel way to look at metagenomic next generation sequencing data and an application in detecting liver cirrhosis.

Early detection of human disease is associated with improved clinical outcomes. However, many diseases are often detected at an advanced, symptomatic stage where patients are past efficacious treatment periods and can result in less favorable outcomes. Therefore, methods that can accurately detect human disease at a presymptomatic stage are urgently needed. Here, we introduce "frequentmers"; short sequences that are specific and recurrently observed in either patient or healthy control samples, but not in both. We showcase the utility of frequentmers for the detection of liver cirrhosis using metagenomic Next Generation Sequencing data from stool samples of patients and controls. We develop classification models for the detection of liver cirrhosis and achieve an AUC score of 0.91 using ten-fold cross-validation. A small subset of 200 frequentmers can achieve comparable results in detecting liver cirrhosis. Finally, we identify the microbial organisms in liver cirrhosis samples, which are associated with the most predictive frequentmer biomarkers.

MPRAbase: A Massively Parallel Reporter Assay Database.

Massively parallel reporter assays (MPRAs) represent a set of high-throughput technologies that measure the functional effects of thousands of sequences/variants on gene regulatory activity. There are several different variations of MPRA technology and they are used for numerous applications, including regulatory element discovery, variant effect measurement, saturation mutagenesis, synthetic regulatory element generation or characterization of evolutionary gene regulatory differences. Despite their many designs and uses, there is no comprehensive database that incorporates the results of these experiments. To address this, we developed MPRAbase, a manually curated database that currently harbors 129 experiments, encompassing 17,718,677 elements tested across 35 cell types and 4 organisms. The MPRAbase web interface (http://www.mprabase.com) serves as a centralized user-friendly repository to download existing MPRA data for independent analysis and is designed with the ability to allow researchers to share their published data for rapid dissemination to the community.

Eligibility for screening with low-dose CT in a real-world cohort of patients with lung cancer in Greece: A brief report.

INTRODUCTION: NELSON and NLST prompted the implementation of lung cancer screening programs in the United States followed by several European countries. This study aimed to assess the sensitivity of different screening criteria among patients with lung cancer in Greece and investigate reasons for ineligibility. METHODS: We performed a retrospective analysis on patients with lung cancer referred to the largest referral center in Athens, Greece, between June 2014 and May 2023. The proportion of patients who would meet the updated USPSTF and NLST criteria was compared to the corresponding proportion of the Greek population over 15 years of age. RESULTS: Out of 2434 patients with lung cancer, 77.4 % (N = 1883) would meet the updated USPSTF criteria, and 58.9 % (N = 1439) would meet the NLST criteria at diagnosis; the corresponding proportions for the Greek population over 15 years would be 13.8 % and 8.2 %, respectively. Ineligible patients were more likely to be female, former or never-smokers, have adenocarcinoma histology, and have driver mutations (p < 0.001). CONCLUSIONS: Although the updated USPSTF criteria demonstrated good sensitivity, a substantial proportion of patients with lung cancer would still not be eligible for screening. Future studies to shape a comprehensive screening strategy should focus on the incorporation of additional risk factors for lung cancer, including air pollution and individual genetic susceptibility.

Surface antibacterial properties enhanced through engineered textures and surface roughness: A review.

The spread of bacteria through contaminated surfaces is a major issue in healthcare, food industry, and other economic sectors. The widespread use of antibiotics is not a sustainable solution in the long term due to the development of antibiotic resistance. Therefore, surfaces with antibacterial properties have the potential to be a disruptive approach to combat microbial contamination. Different methods and approaches have been studied to impart or enhance antibacterial properties on surfaces. The surface roughness and texture are inherent parameters that significantly impact the antibacterial properties of a surface. They are also directly related to the previously employed machining and treatment methods. This review article discusses the correlation between surface roughness and antibacterial properties is presented and discussed. It begins with an introduction to the concepts of surface roughness and texture, followed by a description of the most commonly utilized machining methods and surface. A thorough analysis of bacterial adhesion and growth is then presented. Finally, the most recent studies in this research area are comprehensively reviewed. The studies are sorted and classified based on the utilized machining and treatment methods, which are divided into mechanical processes, surface treatments and coatings. Through the systematic review and record of the recent advances, the authors aim to assist and promote further research in this very promising and extremely important direction, by providing a systematic review of recent advances.

The Efficacy of Tumor Mutation Burden as a Biomarker of Response to Immune Checkpoint Inhibitors.

Cancer is one of the leading causes of death in the world; therefore, extensive research has been dedicated to exploring potential therapeutics, including immune checkpoint inhibitors (ICIs). Initially, programmed-death ligand-1 was the biomarker utilized to predict the efficacy of ICIs. However, its heterogeneous expression in the tumor microenvironment, which is critical to cancer progression, promoted the exploration of the tumor mutation burden (TMB). Research in various cancers, such as melanoma and lung cancer, has shown an association between high TMB and response to ICIs, increasing its predictive value. However, the TMB has failed to predict ICI response in numerous other cancers. Therefore, future research is needed to analyze the variations between cancer types and establish TMB cutoffs in order to create a more standardized methodology for using the TMB clinically. In this review, we aim to explore current research on the efficacy of the TMB as a biomarker, discuss current approaches to overcoming immunoresistance to ICIs, and highlight new trends in the field such as liquid biopsies, next generation sequencing, chimeric antigen receptor T-cell therapy, and personalized tumor vaccines.

Quasi-prime peptides: identification of the shortest peptide sequences unique to a species.

Determining the organisms present in a biosample has many important applications in agriculture, wildlife conservation, and healthcare. Here, we develop a universal fingerprint based on the identification of short peptides that are unique to a specific organism. We define quasi-prime peptides as sequences that are found in only one species, and we analyzed proteomes from 21 875 species, from viruses to humans, and annotated the smallest peptide kmer sequences that are unique to a species and absent from all other proteomes. We also perform simulations across all reference proteomes and observe a lower than expected number of peptide kmers across species and taxonomies, indicating an enrichment for nullpeptides, sequences absent from a proteome. For humans, we find that quasi-primes are found in genes enriched for specific gene ontology terms, including proteasome and ATP and GTP catalysis. We also provide a set of quasi-prime peptides for a number of human pathogens and model organisms and further showcase its utility via two case studies for Mycobacterium tuberculosis and Vibrio cholerae, where we identify quasi-prime peptides in two transmembrane and extracellular proteins with relevance for pathogen detection. Our catalog of quasi-prime peptides provides the smallest unit of information that is specific to a single organism at the protein level, providing a versatile tool for species identification.

Transcription factor binding site orientation and order are major drivers of gene regulatory activity.

The gene regulatory code and grammar remain largely unknown, precluding our ability to link phenotype to genotype in regulatory sequences. Here, using a massively parallel reporter assay (MPRA) of 209,440 sequences, we examine all possible pair and triplet combinations, permutations and orientations of eighteen liver-associated transcription factor binding sites (TFBS). We find that TFBS orientation and order have a major effect on gene regulatory activity. Corroborating these results with genomic analyses, we find clear human promoter TFBS orientation biases and similar TFBS orientation and order transcriptional effects in an MPRA that tested 164,307 liver candidate regulatory elements. Additionally, by adding TFBS orientation to a model that predicts expression from sequence we improve performance by 7.7%. Collectively, our results show that TFBS orientation and order have a significant effect on gene regulatory activity and need to be considered when analyzing the functional effect of variants on the activity of these sequences.