Computational Identification of Novel Genes: Current and Future Perspectives

In silico characterization of five novel disease-resistance proteins in Oryza sativa sp. japonica against bacterial leaf blight and rice blast diseases

In the current study, gene network analysis revealed five novel disease-resistance proteins against bacterial leaf blight (BB) and rice blast (RB) diseases caused by Xanthomonas oryzae pv. oryzae (Xoo) and Magnaporthe oryzae (M. oryzae), respectively. In silico modeling, refinement, and model quality assessment were performed to predict the best structures of these five proteins and submitted to ModelArchive for future use. An in-silico annotation indicated that the five proteins functioned in signal transduction pathways as kinases, phospholipases, transcription factors, and DNA-modifying enzymes. The proteins were localized in the nucleus and plasma membrane. Phylogenetic analysis showed the evolutionary relation of the five proteins with disease-resistance proteins (XA21, OsTRX1, PLD, and HKD-motif-containing proteins). This indicates similar disease-resistant properties between five unknown proteins and their evolutionary-related proteins. Furthermore, gene expression profiling of these proteins using public microarray data showed their differential expression under Xoo and M. oryzae infection. This study provides an insight into developing disease-resistant rice varieties by predicting novel candidate resistance proteins, which will assist rice breeders in improving crop yield to address future food security through molecular breeding and biotechnology.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-023-03893-5.

A review of standardized high-throughput cardiovascular phenotyping with a link to metabolism in mice

Cardiovascular diseases cause a high mortality rate worldwide and represent a major burden for health care systems. Experimental rodent models play a central role in cardiovascular disease research by effectively simulating human cardiovascular diseases. Using mice, the International Mouse Phenotyping Consortium (IMPC) aims to target each protein-coding gene and phenotype multiple organ systems in single-gene knockout models by a global network of mouse clinics. In this review, we summarize the current advances of the IMPC in cardiac research and describe in detail the diagnostic requirements of high-throughput electrocardiography and transthoracic echocardiography capable of detecting cardiac arrhythmias and cardiomyopathies in mice. Beyond that, we are linking metabolism to the heart and describing phenotypes that emerge in a set of known genes, when knocked out in mice, such as the leptin receptor (Lepr), leptin (Lep), and Bardet-Biedl syndrome 5 (Bbs5). Furthermore, we are presenting not yet associated loss-of-function genes affecting both, metabolism and the cardiovascular system, such as the RING finger protein 10 (Rfn10), F-box protein 38 (Fbxo38), and Dipeptidyl peptidase 8 (Dpp8). These extensive high-throughput data from IMPC mice provide a promising opportunity to explore genetics causing metabolic heart disease with an important translational approach.

Functional metagenomics uncovers nitrile-hydrolysing enzymes in a coal metagenome

Introduction: Nitriles are the most toxic compounds that can lead to serious human illness through inhalation and consumption due to environmental pollution. Nitrilases can highly degrade nitriles isolated from the natural ecosystem. In the current study, we focused on the discovery of novel nitrilases from a coal metagenome using in silico mining.

Methods: Coal metagenomic DNA was isolated and sequenced on the Illumina platform. Quality reads were assembled using MEGAHIT, and statistics were checked using QUAST. Annotation was performed using the automated tool SqueezeMeta. The annotated amino acid sequences were mined for nitrilase from the unclassified organism. Sequence alignment and phylogenetic analyses were carried out using ClustalW and MEGA11. Conserved regions of the amino acid sequences were identified using InterProScan and NCBI-CDD servers. The physicochemical properties of the amino acids were measured using ExPASy’s ProtParam. Furthermore, NetSurfP was used for 2D structure prediction, while AlphaFold2 in Chimera X 1.4 was used for 3D structure prediction. To check the solvation of the predicted protein, a dynamic simulation was conducted on the WebGRO server. Ligands were extracted from the Protein Data Bank (PDB) for molecular docking upon active site prediction using the CASTp server.

Results and discussion:In silico mining of annotated metagenomic data revealed nitrilase from unclassified Alphaproteobacteria. By using the artificial intelligence program AlphaFold2, the 3D structure was predicted with a per-residue confidence statistic score of about 95.8%, and the stability of the predicted model was verified with molecular dynamics for a 100-ns simulation. Molecular docking analysis determined the binding affinity of a novel nitrilase with nitriles. The binding scores produced by the novel nitrilase were approximately similar to those of the other prokaryotic nitrilase crystal structures, with a deviation of ±0.5.

Significance of microbial genome in environmental remediation

Environmental pollutants seriously threaten the ecosystem and health of various life forms, particularly with the rapid industrialization and emerging population. Conventionally physical and chemical strategies are being opted for the removal of these pollutants. Bioremediation, through several advancements, has been a boon to combat the existing threat faced today. Microbes with enzymes degrade various pollutants and utilize them as a carbon and energy source. With the existing demand and through several research explorations, Genetically Engineered Microorganisms (GEMs) have paved to be a successful approach to abate pollution through bioremediation. The genome of the microbe determines its biodegradative nature. Thus, methods including pure culture techniques and metagenomics are used for analyzing the genome of microbes, which provides information about catabolic genes. The information obtained along with the aid of biotechnology helps to construct GEMs that are cost-effective and safer thereby exhibiting higher degradation of pollutants. The present review focuses on the role of microbes in the degradation of environmental pollutants, role of evolution in habitat and adaptation of microbes, microbial degenerative genes, their pathways, and the efficacy of recombinant DNA (rDNA) technology for creating GEMs for bioremediation. The present review also provides a gist of existing GEMs for bioremediation and their limitations, thereby providing a future scope of implementation of these GEMs for a sustainable environment.

Origin of an antifreeze protein gene in response to Cenozoic climate change

Antifreeze proteins (AFPs) inhibit ice growth within fish and protect them from freezing in icy seawater. Alanine-rich, alpha-helical AFPs (type I) have independently (convergently) evolved in four branches of fishes, one of which is a subsection of the righteye flounders. The origin of this gene family has been elucidated by sequencing two loci from a starry flounder, Platichthys stellatus, collected off Vancouver Island, British Columbia. The first locus had two alleles that demonstrated the plasticity of the AFP gene family, one encoding 33 AFPs and the other allele only four. In the closely related Pacific halibut, this locus encodes multiple Gig2 (antiviral) proteins, but in the starry flounder, the Gig2 genes were found at a second locus due to a lineage-specific duplication event. An ancestral Gig2 gave rise to a 3-kDa "skin" AFP isoform, encoding three Ala-rich 11-a.a. repeats, that is expressed in skin and other peripheral tissues. Subsequent gene duplications, followed by internal duplications of the 11 a.a. repeat and the gain of a signal sequence, gave rise to circulating AFP isoforms. One of these, the "hyperactive" 32-kDa Maxi likely underwent a contraction to a shorter 3.3-kDa "liver" isoform. Present day starry flounders found in Pacific Rim coastal waters from California to Alaska show a positive correlation between latitude and AFP gene dosage, with the shorter allele being more prevalent at lower latitudes. This study conclusively demonstrates that the flounder AFP arose from the Gig2 gene, so it is evolutionarily unrelated to the three other classes of type I AFPs from non-flounders. Additionally, this gene arose and underwent amplification coincident with the onset of ocean cooling during the Cenozoic ice ages.

Foster thy young: enhanced prediction of orphan genes in assembled genomes

Proteins encoded by newly-emerged genes ('orphan genes') share no sequence similarity with proteins in any other species. They provide organisms with a reservoir of genetic elements to quickly respond to changing selection pressures. Here, we systematically assess the ability of five gene prediction pipelines to accurately predict genes in genomes according to phylostratal origin. BRAKER and MAKER are existing, popular ab initio tools that infer gene structures by machine learning. Direct Inference is an evidence-based pipeline we developed to predict gene structures from alignments of RNA-Seq data. The BIND pipeline integrates ab initio predictions of BRAKER and Direct inference; MIND combines Direct Inference and MAKER predictions. We use highly-curated Arabidopsis and yeast annotations as gold-standard benchmarks, and cross-validate in rice. Each pipeline under-predicts orphan genes (as few as 11 percent, under one prediction scenario). Increasing RNA-Seq diversity greatly improves prediction efficacy. The combined methods (BIND and MIND) yield best predictions overall, BIND identifying 68% of annotated orphan genes, 99% of ancient genes, and give the highest sensitivity score regardless dataset in Arabidopsis. We provide a light weight, flexible, reproducible, and well-documented solution to improve gene prediction.

Self-assembled peptide and protein nanostructures for anti-cancer therapy: Targeted delivery, stimuli-responsive devices and immunotherapy

Self-assembled peptides and proteins possess tremendous potential as targeted drug delivery systems and key applications of these well-defined nanostructures reside in anti-cancer therapy. Peptides and proteins can self-assemble into nanostructures of diverse sizes and shapes in response to changing environmental conditions such as pH, temperature, ionic strength, as well as host and guest molecular interactions; their countless benefits include good biocompatibility and high loading capacity for hydrophobic and hydrophilic drugs. These self-assembled nanomaterials can be adorned with functional moieties to specifically target tumor cells. Stimuli-responsive features can also be incorporated with respect to the tumor microenvironment. This review sheds light on the growing interest in self-assembled peptides and proteins and their burgeoning applications in cancer treatment and immunotherapy.

Overview of the betta fish genome regarding species radiation, parental care, behavioral aggression, and pigmentation model relevant to humans

BACKGROUND

The Siamese fighting fish (Betta splendens, also known as the betta) is well known in aquarium markets, and also presents an exciting new research model for studying parental care, aggressive behavior, and cryptically diverse pigmentation. However, concentrated efforts are required, both in the context of conservation biology and in its genetics, to address the problems of ongoing outbreeding depression, loss of biodiversity, and lack of scientific biological information.

OBJECTIVE

The evolutionary dynamics of the betta must be better understood at the genomic scale in order to resolve the phylogenetic status of unrecognized species, develop molecular markers to study variation in traits, and identify interesting sets of genes encoding various bioresource functions.

METHODS

The recent revolution in multi-omics approaches such as genomics, transcriptomics, epigenomics, and proteomics has uncovered genetic diversity and gained insights into many aspects of betta bioresources.

RESULTS

Here, we present current research and future plans in an ongoing megaproject to characterize the betta genome as de novo assemblies, genes and repeat annotations, generating data to study diverse biological phenomena. We highlight key questions that require answers and propose new directions and recommendations to develop bioresource management to protect and enhance the betta genus.

CONCLUSION

Successful accomplishment of these plans will allow the creation of a reference annotated genome and provide valuable information at the molecular level that can be utilized to sustain biodiversity and eco-management of the betta to improve breeding programs for future biomedical research.

Advances in the Bioinformatics Knowledge of mRNA Polyadenylation in Baculovirus Genes

Baculoviruses are a group of insect viruses with large circular dsDNA genomes exploited in numerous biotechnological applications, such as the biological control of agricultural pests, the expression of recombinant proteins or the gene delivery of therapeutic sequences in mammals, among others. Their genomes encode between 80 and 200 proteins, of which 38 are shared by all reported species. Thanks to multi-omic studies, there is remarkable information about the baculoviral proteome and the temporality in the virus gene expression. This allows some functional elements of the genome to be very well described, such as promoters and open reading frames. However, less information is available about the transcription termination signals and, consequently, there are still imprecisions about what are the limits of the transcriptional units present in the baculovirus genomes and how is the processing of the 3′ end of viral mRNA. Regarding to this, in this review we provide an update about the characteristics of DNA signals involved in this process and we contribute to their correct prediction through an exhaustive analysis that involves bibliography information, data mining, RNA structure and a comprehensive study of the core gene 3′ ends from 180 baculovirus genomes.

De novo sequencing of proteins by mass spectrometry

INTRODUCTION

Proteins are crucial for every cellular activity and unraveling their sequence and structure is a crucial step to fully understand their biology. Early methods of protein sequencing were mainly based on the use of enzymatic or chemical degradation of peptide chains. With the completion of the human genome project and with the expansion of the information available for each protein, various databases containing this sequence information were formed.

AREAS COVERED

De novo protein sequencing, shotgun proteomics and other mass-spectrometric techniques, along with the various software are currently available for proteogenomic analysis. Emphasis is placed on the methods for de novo sequencing, together with potential and shortcomings using databases for interpretation of protein sequence data.

EXPERT OPINION

As mass-spectrometry sequencing performance is improving with better software and hardware optimizations, combined with user-friendly interfaces, de-novo protein sequencing becomes imperative in shotgun proteomic studies. Issues regarding unknown or mutated peptide sequences, as well as, unexpected post-translational modifications (PTMs) and their identification through false discovery rate searches using the target/decoy strategy need to be addressed. Ideally, it should become integrated in standard proteomic workflows as an add-on to conventional database search engines, which then would be able to provide improved identification.

Global Role of Crop Genomics in the Face of Climate Change

The development of climate change resilient crops is necessary if we are to meet the challenge of feeding the growing world's population. We must be able to increase food production despite the projected decrease in arable land and unpredictable environmental conditions. This review summarizes the technological and conceptual advances that have the potential to transform plant breeding, help overcome the challenges of climate change, and initiate the next plant breeding revolution. Recent developments in genomics in combination with high-throughput and precision phenotyping facilitate the identification of genes controlling critical agronomic traits. The discovery of these genes can now be paired with genome editing techniques to rapidly develop climate change resilient crops, including plants with better biotic and abiotic stress tolerance and enhanced nutritional value. Utilizing the genetic potential of crop wild relatives (CWRs) enables the domestication of new species and the generation of synthetic polyploids. The high-quality crop plant genome assemblies and annotations provide new, exciting research targets, including long non-coding RNAs (lncRNAs) and cis-regulatory regions. Metagenomic studies give insights into plant-microbiome interactions and guide selection of optimal soils for plant cultivation. Together, all these advances will allow breeders to produce improved, resilient crops in relatively short timeframes meeting the demands of the growing population and changing climate.

A report on DNA sequence determinants in gene expression

The biased usage of nucleotides in coding sequence and its correlation with gene expression has been observed in several studies. A complex set of interactions between genes and other components of the expression system determine the amount of proteins produced from coding sequences. It is known that the elongation rate of polypeptide chain is affected by both codon usage bias and specific amino acid compositional constraints. Therefore, it is of interest to review local DNA-sequence elements and other positional as well as combinatorial constraints that play significant role in gene expression.

Nutrition-responsive gene expression and the developmental evolution of insect polyphenism

Nutrition-responsive development is a ubiquitous and highly diversified example of phenotypic plasticity, yet its underlying molecular and developmental mechanisms and modes of evolutionary diversification remain poorly understood. We measured genome-wide transcription in three closely related species of horned beetles exhibiting strikingly diverse degrees of nutrition responsiveness in the development of male weaponry. We show that (1) counts of differentially expressed genes between low- and high-nutritional backgrounds mirror species-specific degrees of morphological nutrition responsiveness; (2) evolutionary exaggeration of morphological responsiveness is underlain by both amplification of ancestral nutrition-responsive gene expression and recruitment of formerly low nutritionally responsive genes; and (3) secondary loss of morphological responsiveness to nutrition coincides with a dramatic reduction in gene expression plasticity. Our results further implicate genetic accommodation of ancestrally high variability of gene expression plasticity in both exaggeration and loss of nutritional plasticity, yet reject a major role of taxon-restricted genes in the developmental regulation and evolution of nutritional plasticity.

Faustovirus E12 Transcriptome Analysis Reveals Complex Splicing in Capsid Gene

Faustoviruses are the first giant viruses of amoebae isolated on Vermamoeba vermiformis. They are distantly related to African swine fever virus, the causative agent of lethal hemorrhagic fever in domestic pigs. Structural studies have shown the presence of a double protein layer encapsidating the double-stranded DNA genome of Faustovirus E12, the prototype strain. The major capsid protein (MCP) forming the external layer has been shown to be 645-amino acid-long. Unexpectedly, its encoding sequence has been found to be scattered along a 17 kbp-large genomic region. Using RNA-seq, we studied expression of Faustovirus E12 genes at nine time points over its entire replicative cycle. Paired-end 250 bp-long read sequencing on MiSeq instrument and double-round spliced alignment enabled the identification of 26 different splice-junctions. Reads corresponding to junctions represented 2% of mapped reads and mostly matched with the predicted MCP encoding sequences. Moreover, our study enabled describing a 1,939 bp-long transcript that corresponds to the MCP, delineating 13 exons. At least two types of introns coexist in the MCP gene: group I introns that can self-splice (n = 5) and spliceosome-like introns with non-canonical splice sites (n = 7). All splice-sites were non-canonical with five types of donor/acceptor splice-sites among which AA/TG was the most frequent association.

Bioinformatic Analyses of Unique (Orphan) Core Genes of the Genus Acidithiobacillus: Functional Inferences and Use As Molecular Probes for Genomic and Metagenomic/Transcriptomic Interrogation

Using phylogenomic and gene compositional analyses, five highly conserved gene families have been detected in the core genome of the phylogenetically coherent genus Acidithiobacillus of the class Acidithiobacillia. These core gene families are absent in the closest extant genus Thermithiobacillus tepidarius that subtends the Acidithiobacillus genus and roots the deepest in this class. The predicted proteins encoded by these core gene families are not detected by a BLAST search in the NCBI non-redundant database of more than 90 million proteins using a relaxed cut-off of 1.0e⁻⁵. None of the five families has a clear functional prediction. However, bioinformatic scrutiny, using pI prediction, motif/domain searches, cellular location predictions, genomic context analyses, and chromosome topology studies together with previously published transcriptomic and proteomic data, suggests that some may have functions associated with membrane remodeling during cell division perhaps in response to pH stress. Despite the high level of amino acid sequence conservation within each family, there is sufficient nucleotide variation of the respective genes to permit the use of the DNA sequences to distinguish different species of Acidithiobacillus, making them useful additions to the armamentarium of tools for phylogenetic analysis. Since the protein families are unique to the Acidithiobacillus genus, they can also be leveraged as probes to detect the genus in environmental metagenomes and metatranscriptomes, including industrial biomining operations, and acid mine drainage (AMD).