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4D-DIA proteomics reveals distinct proteolytic landscapes induced by mechanical stress, Agrobacterium, and a viral capsid precursor.

Nicotiana benthamiana is a widely used platform for plant molecular farming, yet recombinant protein yields are frequently compromised by the host's innate defense mechanisms, particularly proteolytic degradation. While the general effects of Agroinfiltration are known, the distinct contributions of mechanical injury, bacterial perception, and product-specific stress remain poorly resolved. Here we utilized high-depth 4D-DIA proteomics to dissect the host response across three dimensions: physical stress (buffer infiltration), pathogen-associated stress (Agrobacterium), and product-associated stress (GFP vs. the FMDV capsid precursor P1_2A). We demonstrate that buffer infiltration is not a neutral event but an independent inducer of cell wall remodeling and oxidative stress. By filtering out these background effects, we defined a core Agrobacterium-responsive proteome characterized by a growth-defense trade-off. We also expanded the known protease repertoire of N. benthamiana to 1,505 enzymes through improved genomic annotation. We found that the expression of the FMDV capsid precursor P1_2A was associated with a distinct and more pronounced protease profile compared to soluble GFP, characterized by the upregulation of subtilases and cysteine proteases. These findings suggest that host proteolytic responses vary with the recombinant cargo, a factor worth considering when designing engineering strategies for the production of complex biopharmaceuticals in plants.

Proteomics↗

Identification of microRNAs and other tiny noncoding RNAs by cDNA cloning.

MicroRNAs (miRNAs) and other small RNAs can be identified by cloning and sequencing cDNAs prepared from the approximately 22-nt fraction of total RNA. Methods are described for the construction of cDNA libraries from small noncoding RNAs through the use of T4 RNA ligase, reverse transcriptase, and polymerase chain reaction. cDNAs are cloned in lambda or plasmid vectors, and the sequences are compared to annotated genomic sequence databases, and analyzed by RNA folding programs to distinguish miRNA sequences from other small RNAs of similar size. Northern blot hybridization is used to confirm the expression of small RNAs in vivo.

3' Untranslated Regions↗

Electrophysiological analysis of neuronal and muscle function in C. elegans.

The nematode Caenorhabditis elegans provides numerous experimental advantages for the identification and characterization of genes required for the function of the nervous system. These advantages include forward and reverse genetic tractability, a relatively simple body plan with an invariant cellular lineage, and a fully sequenced and well-annotated genome. However, one limitation of C. elegans is the relative scarcity of electrophysiological data from excitable cells. To address this limitation, high-resolution cellular techniques for probing the roles of specific gene products in the C. elegans nervous system have been recently developed. This chapter will provide an overview of the technical requirements for patch-clamp electrophysiological analysis of C. elegans neurons and muscle cells, as well as provide some illustrative examples of insights gained from the pairing of electrophysiological techniques with molecular and genetic analysis.

Animals↗

Channeling studies in yeast: yeast as a model for channelopathies?

Regulation of the concentration of ions within a cell is mediated by their specific transport and sequestration across cellular membranes. This regulation constitutes a major factor in the maintenance of correct cellular homeostasis, with the transport occurring through the action of a large number of different channel proteins localized to the plasma membrane as well as to various organelles. These ion channels vary in specificity from broad (cationic vs anionic) to highly selective (chloride vs sodium). Mutations in many of these channels result in a large number of human diseases, collectively termed channelopathies. Characterization of many of these channels has been undertaken in a variety of both prokaryotic and eukaryotic organisms. Among these organisms is the budding yeast Saccharomyces cerevisiae. Possessing a fully annotated genome, S. cerevisiae would appear to be an ideal organism in which to study this class of proteins associated to diseases. We have compiled and reviewed a list of yeast ion channels, each possessing a human homolog implicated in a channelopathy. Although yeast has been used for the study of other human disease, it has been under utilized for channelopathy research. The utility of using yeast as a model system for studying ion channels associated to human disease is illustrated using yeast lacking the GEF1 gene product that encodes the human homolog to the chloride channel CLC-3.

Animals↗

Cancer target discovery using SAGE.

Cancer is a genetic disease. Genetic events including mutations, chromosomal gains, losses and rearrangements, along with epigenetic alterations, lead to significant transcriptional changes in cancer cells. Changes in the expression of many genes associated with the onset and progression of cancer likely contribute to the cancerous phenotype. SAGE (Serial Analysis of Gene Expression) is an expression profiling method that allows for global, unbiased and quantitative characterisation of transcriptomes. The expression of thousands of genes can be analysed simultaneously without prior knowledge of their sequence, thus leading to the discovery of novel transcripts. In addition to characterising normal and malignant gene expression patterns, SAGE can be used to identify downstream targets of tumour suppressors and oncogenes and further annotate genomes. Comprehensive analyses of expression profiles using SAGE will yield many new diagnostic and prognostic markers as well as therapeutic targets in cancer.

Antineoplastic Agents↗

Serial analysis of gene expression in eukaryotic pathogens.

The tag-based method of serial analysis of gene expression (SAGE) has been used to measure mRNA abundance and differential expression in a variety of organisms including several parasites and fungal pathogens. SAGE is based on the collection of short sequence tags as a measure of transcript abundance and the method provides an alternative, and in some instances, complementary approach to array-based methods of measuring differential gene expression. These methods are being used to improve our molecular understanding of the pathogenesis of eukaryotic microbes and SAGE in particular presents valuable opportunities for gene discovery and genome annotation. For eukaryotic pathogens, the SAGE method has been employed for the parasites Plasmodium falciparum, Toxoplasma gondii and Giardia lamblia, as well as fungal pathogens of plants (Magnaporthe grisea, Blumeria graminis, Ustilago maydis) and humans (Cryptococcus neoformans, Coccidiodes posadasii, Trichophyton rubrum). The accumulating information promises to speed the identification of key pathogen functions for virulence and proliferation in the host with the hope that some of these will represent important targets for drug and vaccine development.

Animals↗

Development and application of in vivo expression technology (IVET) for analysing microbial gene expression in complex environments.

Establishing the mechanisms by which microbes interact with their environment, including eukaryotic hosts, is a major challenge that is essential for the economic utilisation of microbes and their products. Techniques for determining global gene expression profiles of microbes, such as microarray analyses, are often hampered by methodological restraints, particularly the recovery of bacterial transcripts (RNA) from complex mixtures and rapid degradation of RNA. A pioneering technology that avoids this problem is In Vivo Expression Technology (IVET). IVET is a 'promoter-trapping' methodology that can be used to capture nearly all bacterial promoters (genes) upregulated during a microbe-environment interaction. IVET is especially useful because there is virtually no limit to the type of environment used (examples to date include soil, oomycete, a host plant or animal) to select for active microbial promoters. Furthermore, IVET provides a powerful method to identify genes that are often overlooked during genomic annotation, and has proven to be a flexible technology that can provide even more information than identification of gene expression profiles. A derivative of IVET, termed resolvase-IVET (RIVET), can be used to provide spatio-temporal information about environment-specific gene expression. More recently, niche-specific genes captured during an IVET screen have been exploited to identify the regulatory mechanisms controlling their expression. Overall, IVET and its various spin-offs have proven to be a valuable and robust set of tools for analysing microbial gene expression in complex environments and providing new targets for biotechnological development.

Anti-Bacterial Agents↗

Ancient genes in contemporary persistent microbial pathogens.

Autotrophs, the earliest prokaryotes, use CO(2) as the sole or the key source in the reductive citric acid cycle for carbon fixation. This pathway, also known as the reductive tricarboxylic acid (rTCA) cycle, has as its center the Krebs cycle running in the reductive direction, using reduced cofactors for energy. During the infection process, persistent pathogenic bacteria like Mycobacterium tuberculosis, Helicobacter pylori, and Salmonella typhi experience diverse and hostile environments both intracellularly (in macrophages) and extracellularly. M. tuberculosis, for example, must adapt to nutrient-deprived, hypoxic conditions in the granuloma. Genomic annotations reveal the presence of the key enzymes of the rTCA cycle--citrate lyase (Enzyme Commission number EC 4.1.3.6) and 2-oxoglutarate synthase (EC 1.2.7.3)--along with the rest of the TCA cycle enzymes. It is possible that there is a metabolic switch to anaerobic respiration in which a complete or a partial TCA cycle may operate in the reductive mode. This switch would both facilitate carbon fixation and restore the balance of oxidative and reductive reactions during environmental transitions, thus enabling the pathogen to survive, grow, and persist. Verification of enzyme function by biochemical investigations and validation of gene essentiality by knockout studies may reveal these enzymes to be rational drug targets for treatment of persistent microbial infections in mechanism-based drug discovery processes.

Archaea↗

Induced Pluripotent Stem Cells in Non-Model Species: Applications and Challenges.

Induced pluripotent stem cells have revolutionized biomedical research-yet the vast majority of life on Earth remains beyond their reach. Non-model species lack the annotated genomes, validated reagents, and species-specific culture infrastructure that make iPSC technology routine in humans and mice, and this infrastructure deficit, compounded by genuine biological differences in pluripotency network architecture across taxa, is what has kept the field narrow. The deep conservation of the core pluripotency network across vertebrates suggests that reprogramming may, in principle, be achievable across a far broader range of species than currently demonstrated-though the extent to which this holds across more divergent taxa remains to be established. This review consolidates current progress and future potential of iPSC technology across five domains: technical reprogramming challenges and advances; conservation applications including genetic rescue, in vitro gametogenesis, and de-extinction; medical applications within a one medicine framework; agricultural applications spanning disease resistance, climate resilience, and cultured meat; and species-specific iPSC-derived systems in ecotoxicology. Throughout, we distinguish what has been demonstrated from what remains aspirational and identify the priorities that will determine whether the iPSC revolution can be extended-rigorously and at scale-beyond model organism research.

Induced Pluripotent Stem Cells↗

Isolation and Characterization of a Naturally Occurring Brevundimonas vesicularis Strain Exhibiting High Phytoene Accumulation.

Phytoene, a colorless precursor of carotenoids, has attracted increasing attention because of its favorable bioavailability, antioxidant activity, and potential applications in functional foods, nutraceuticals, and animal nutrition. However, its industrial utilization remains limited by low natural abundance and the dependence of current production strategies on genetic engineering or metabolic pathway manipulation. In this study, we identified and characterized a naturally occurring Brevundimonas vesicularis strain (Bv-xms2024) exhibiting pronounced phytoene accumulation without genetic modification. The strain was comprehensively characterized using morphological, biochemical, molecular, genomic, metabolomic, and transcriptional analyses. Quantitative LC-MS/MS analysis demonstrated that Bv-xms2024 accumulated phytoene to 420.42 ± 98.11 μg/g dry biomass after 96 h of cultivation, substantially exceeding the levels of downstream carotenoids, including β-carotene and astaxanthin. Optimization of cultivation parameters identified 25 °C, pH 7.0, and 96 h as the optimal conditions for phytoene accumulation, while serial passaging confirmed stable production over 20 generations. Genome annotation identified the carotenoid biosynthetic gene repertoire, while RT-qPCR analysis revealed a temporal shift from early upregulation of crtE and crtB to later upregulation of downstream pathway genes, consistent with the observed phytoene-dominant carotenoid profile. Short-term tolerance evaluations in mice and chickens revealed no observable adverse effects under the tested conditions. Collectively, these findings identify Bv-xms2024 as a promising natural microbial resource for phytoene production and provide a basis for further process development and strain-level safety evaluation.

Brevundimonas vesicularis↗

A comparative guide to gene prediction tools for the bioinformatics amateur.

Several hundred programs using different algorithms have been designed to predict individual coding features within any genomic sequence, but none of these tools covers all aspects of a gene or is 100% accurate in its prediction. Automated simultaneous processing of the results from a number of these programs minimizes the chance of a false positive prediction and quickly generates integrated data. We report here on the analysis of two known genes in 5 and 25 kb segments of genomic sequence using four genome annotation packages, NIX, RUMMAGE, Genotator and EMBOSS. Gene predictions were confirmed using cDNA sequences and a comparison was made between the packages. This study showed a similarity in the ability of NIX, RUMMAGE and Genotator to predict well-characterised genes and basic structures, but poor exon prediction for a small, 3 exon gene. However, the BLAST subprograms of all three packages correctly identified the 3 exons. In addition, EST BLAST subprograms identified a previously undescribed, possible 5' untranslated exon for the smaller gene and a number of putative alternatively spliced exons in the larger gene. Overall, NIX was found to be the most user-friendly package, in terms of easy access to databases and the interactive graphical display of results.

Algorithms↗

How Not to be Seen: Predicting Unseen Enzyme Functions using Contrastive Learning.

MOTIVATION: Predicting enzyme function from its sequence is still an unsolved problem in the life sciences. Moreover, with the explosion of annotated genome data, we are inundated with potential enzymatic sequences that have not yet been biochemically characterized. While it is not possible to assign a not-yet-existing label to such a sequence, there is high value in placing the sequence as accurately as possible in known function space. Doing so can help provide more accurate falsifiable hypotheses for experimentalists wishing to characterize enzymes from specific functional families. RESULTS: Here we present a contrastive learning algorithm for predicting enzyme function from sequence. Our method, EnzPlacer, predicts the third, second, and first EC numbers for a protein whose fourth EC number is not in the training corpus. This novel prediction mechanism accurately places a protein sequence within a narrowed-down functional context, even if the precise function remains unknown. AVAILABILITY: EnzPlacer is available from https://github.com/drxiangma/EnzPlacer under a GPL3 license.

Contrastive learning↗

Insights from MHC-bound peptides.

Cytotoxic T cells recognize short antigenic peptides, the processing products of protein antigens, when they are bound to major histocompatibility complex (MHC) class I molecules. Peptide binding to MHC molecules has been studied extensively in numerous laboratories, providing vast amounts of sequence and structure data that have been used as a rich source for bioinformatic research. MHC-bound peptides and their flanking sequences provide information about the sequence requirements of the different processing stages, in particular, the cleavage by the proteasome and the binding to MHC molecules. Elucidation of these sequence requirements sheds light on the evolutionary forces that have shaped and designed these peptides, and should lead to the development of an integrative predictive algorithm. Remarkably, the peptide sequence and structure data are also valuable for the study of biological questions that are apparently unrelated to cellular immunity, namely, sequence-structure relationship and genome annotation. Here we describe our computational analyses of MHC-bound peptides, applied to all these biological topics.

Allergy and Immunology↗

[ClusterTree-RS: the binary tree algorithm for identification of co-regulated genes by clustering regulatory signals].

Identification of groups of co-regulated genes (regulons) is an important part of studying transcriptional regulation. One possible approach is to cluster regulatory sites that were found using experimental or computational techniques, such as phylogenetic footprinting. This strategy doesn't require a priori knowledge about co-regulation and allows finding putative new members of known groups of co-regulated genes (i.e. a new regulon). Also, it allows finding new putative regulons, which is especially important for poorly annotated genomes. We have developed ClusterTree-RS, an algorithm for clustering regulatory signals using binary trees; it is presented in this paper along with some testing results on simulated and real data. The algorithm is implemented in Java and took about 2 hours 40 minutes to cluster 1500 input signals on a computer with AMD Athlon 1.91 GHz CPU.

Algorithms↗

[Stress proteins of Bifidobacterium longum NCC2705].

Stress proteins of Bifidobacterium longum strain NCC2705 were identified and characterized during stationary phase. According to the proteomic map of L. lactics IL1403 and theoretical Mr/pl of stress proteins in B. longum NCC2705 genome annotation, spots of stress proteins in gels were localized, and proteins were identified by matrix-assisted laser desorption/ionization time of flight (MALDI-TOF) and/or ESI-MS/MS mass spectrometry. For protein identification by peptide mass fingerprinting, peptide masses were searched against database of B. longum NCC2705 by Mascot licensed in-house. 44 spots representing 8 protein entries have been identified, these proteins were hydrophilic proteins and predicted acid proteins. Spot and protein analysis revealed that post-translational modifications might be common in these proteins. Except for DnaJ, the stress proteins were encoded by genes with CAI value above 0.5, and represented a large proportion of the most abundant proteins. Moreover, the results of scavenging effects on free radicals in vitro showed that B. longum NCC2705 can inhibit fatty acid oxidation and scavenge DPPH, but they scavenge weakly active oxygen free radicals. We identified a key protein that can reverse oxidative damage to proteins and lipids: alkyl hydroperoxide reductase (ahpC, BL0615)synthesized under our experimental conditions.

Bacterial Proteins↗

Proclass protein family database: new version with motif alignments.

ProClass is a protein family database which organizes non-redundant sequence entries into families defined collectively by the ProSite patterns and PIR superfamilies. The database consists of about 100,000 entries, more than half of which are classified in about 3,000 families. The new version includes links to various protein family/domain and structural class databases and contains gapped motif alignments for all ProSite patterns. The motif sequences are retrieved from both SwissProt and PIR-international databases, including numerous new members detected by our GeneFIND family identification system. The motif collection represents a 50% increase from those catalogued in ProSite. The ProClass database can be used to maximize family information retrieval, help organize protein sequence databases, and support full-scale genomic annotation. The database and its query program are freely available for on-line record retrieval and direct file transfer from our WWW server at http:/(/)diana.uthct.edu/proclass.html+ ++.

Amino Acid Sequence↗

Toward a functional annotation of the human genome using artificial transcription factors.

We have developed a novel, high-throughput approach to collecting randomly perturbed gene-expression profiles from the human genome.A human 293 cell library that stably expresses randomly chosen zinc-finger transcription factors was constructed, and the expression profile of each cell line was obtained using cDNA microarray technology.Gene expression profiles from a total of 132 cell lines were collected and analyzed by (1) a simple clustering method based on expression-profile similarity, and (2) the shortest-path analysis method. These analyses identified a number of gene groups, and further investigation revealed that the genes that were grouped together had close biological relationships. The artificial transcription factor-based random genome perturbation method thus provides a novel functional genomic tool for annotation and classification of genes in the human genome and those of many other organisms.

Antigens, Neoplasm↗

A Strain of Mycoplasma hominis Causing Pleuropneumonia Infection in an Immunocompetent Patient and Recent Epidemiological Trends: Implications for Clinical Management.

Mycoplasma hominis (M. hominis) is an opportunistic pathogen linked to urogenital and neonatal infections; however, limited genetic and epidemiological data are available. Extragenital infections in healthy adults are rare, and effective antibiotics are species-specific, complicating diagnosis and treatment. Hence, this study aimed to elucidate the clinical process, update the epidemiological characteristics, and investigate the genomic features of a fluoroquinolone-resistant M. hominis isolate from an immunocompetent patient with pleuropneumonia in China. The M. hominis isolate ZY_MH01 was recovered from pleural fluid and was identified by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) and Whole Genome Sequencing (WGS). The completed genome was annotated using the NCBI Prokaryotic Genome Annotation Pipeline (PGAP). Snippy v4.4.5 was utilized to conduct a core genome single nucleotide polymorphism (cgSNP) analysis between ZY_MH01 and 144 M. hominis strains from the NCBI GenBank database. Subsequently, phylogenies were constructed using IQ-TREE v3.1.2 and visualized by iTOL. Antimicrobial resistance determinants were identified using strict criteria of Comprehensive Antibiotic Resistance Database (CARD) RGI 6.0.5 (Web portal) and broth microdilution test. Virulence genes were screened using Abricate v1.0.1 against the Virulence Factor Database (VFDB). A total of 42 strains (including ZY_MH01) from Genbank with an assembly level of Complete or Chromosome were re-annotated using Prokka v1.2.0 and pangenome analysis was performed using the Roary. The core genome constitutes only 17.1%, which may contribute to the unusually high level of polymorphism observed among M. hominis strains. No antibiotic resistance genes or virulence genes were detected in the genome of ZY_MH01. However, some resistance-associated mutations of gene parC and gyrA in the Quinolone Resistance Determining Region (QRDR) were identified. Phylogenetic analysis indicates that strains originating from the same geographic region typically exhibit reduced genetic distances; this trend is especially pronounced in regions with a higher number of publicly available strain sequences. In specific circumstances, when conventional broad-spectrum antibiotics are ineffective, even immunocompetent patients should consider the possibility of M. hominis infection. This study presents a detailed account of the diagnostic and therapeutic course of a pleuropneumonia infection caused by M. hominis in an immunocompetent patient, and performs an epidemiological analysis of all M. hominis sequences that have been recently made publicly available.

Humans↗