Complex Genetic Networks Research Articles

Genomic Insights into Staphylococcus aureus: Mechanisms of Antibiotic Resistance and Virulence Gene Expression

Staphylococcus aureus is a major human pathogen responsible for a wide range of infections, from mild skin conditions to severe systemic diseases. The increasing prevalence of antibiotic-resistant strains, such as methicillin-resistant S. aureus (MRSA), poses significant challenges to global healthcare systems. This review provides a comprehensive analysis of the genomic mechanisms underpinning antibiotic resistance and virulence in S. aureus. Key resistance mechanisms include the acquisition of resistance genes through horizontal gene transfer, mutations in target sites, and the overexpression of efflux pumps. Additionally, the regulation of virulence factors, such as toxins, adhesion molecules, and enzymes, is controlled by complex genetic networks, including quorum sensing and global regulators like the agr and sar systems. Advances in whole-genome sequencing have facilitated a deeper understanding of the genetic diversity and adaptability of S. aureus. These insights are essential for developing innovative therapeutic strategies and mitigating the impact of this pathogen on public health.

TRANSCRIPTIONAL ANALYSIS OF SOYBEAN (Glycine max) GENES RELATED TO WATER DEFICIT

ABSTRACT The soybean crop has been gaining worldwide prominence, being widely disseminated due to its various forms of use in different segments. Genetic and environmental factors are decisive in the quality of this culture. A feature related to the environmental factor that has gained prominence is the water deficit. Molecular events are initiated by the perception of water stress, involving a complex genetic network. Studies in recent decades have already identified some genes related to water stress in plants, it is known that the dehydration-responsive element binding protein (DREB) plays an important role in the response to water deficit. Therefore, this work aimed to analyze the expression of genes related to water deficit in soybean. For the analysis of gene expression, leaves of soybean (Glycine max (L.) Merrill), cultivar M9144 RR, submitted to the following treatments were used: 25V25R – plants subjected to water deficit throughout the cycle, being irrigated with 25% of ETpc and 100V100R – plants that did not experience water deficit, being irrigated with 100% of ETpc throughout the cycle. The quantification of the relative expression of the genes GmDREB1 and GmDREB5 showed that the water stress suffered by the cultivar was greater in the reproductive stage. Keywords: Transcription factors, development stages, gene expression.

Antifungal Drug Resistance in Candida albicans: Identifying Novel Targets for the Development of Effective Antifungal Agents.

Candidiasis, a fungal infection initiated primarily through Candida albicans, affects various portions of the human body and is particularly prevalent in immunocompromised individuals. The pathogenicity of C. albicans is facilitated by numerous virulence causes, including adhesins, morphogenesis, and phenotypic switching. The organism’s capability in the direction of switching between yeast and hyphal forms contributes to the severity of infections. The appearance of resistant strains has rendered current treatments less effective, necessitating the exploration of new drug targets and the progress of novel antifungal agents. Antifungal drug resistance is a multifaceted phenomenon involving genetic mutations, overexpression of efflux pumps, epigenetic changes, and biofilm formation, all regulated by complex genetic and transcriptional networks. These resistance mechanisms can cause treatment failures, highlighting the need for new antifungal agents and improved diagnostic tools. The identification of potential drug targets in C. albicans is critical due to increasing resistance to existing antifungal agents. Recent studies have identified promising targets, for example the riboflavin metabolic pathway and unique protein kinases involved in regulating virulence and pathogenicity. Developing new antifungals is difficult due to C. albicans’ eukaryotic nature and resistance. Ongoing research is essential to find novel targets and strategies, especially with the limited antifungal drug classes available.

Genetic, molecular and physiological crosstalk during drought tolerance in maize (Zea mays): pathways to resilient agriculture.

This review comprehensively elucidates maize drought tolerance mechanisms, vital for global food security. It highlights genetic networks, key genes, CRISPR-Cas applications, and physiological responses, guiding resilient variety development. Maize, a globally significant crop, confronts the pervasive challenge of drought stress, impacting its growth and yield significantly. Drought, an important abiotic stress, triggers a spectrum of alterations encompassing maize's morphological, biochemical, and physiological dimensions. Unraveling and understanding these mechanisms assumes paramount importance for ensuring global food security. Approaches like developing drought-tolerant varieties and harnessing genomic and molecular applications emerge as effective measures to mitigate the negative effects of drought. The multifaceted nature of drought tolerance in maize has been unfolded through complex genetic networks. Additionally, quantitative trait loci mapping and genome-wide association studies pinpoint key genes associated with drought tolerance, influencing morphophysiological traits and yield. Furthermore, transcription factors like ZmHsf28, ZmNAC20, and ZmNF-YA1 play pivotal roles in drought response through hormone signaling, stomatal regulation, and gene expression. Genes, such as ZmSAG39, ZmRAFS, and ZmBSK1, have been reported to be pivotal in enhancing drought tolerance through diverse mechanisms. Integration of CRISPR-Cas9 technology, targeting genes like gl2 and ZmHDT103, emerges as crucial for precise genetic enhancement, highlighting its role in safeguarding global food security amid pervasive drought challenges. Thus, decoding the genetic and molecular underpinnings of drought tolerance in maize sheds light on its resilience and paves the way for cultivating robust and climate-smart varieties, thus safeguarding global food security amid climate challenges. This comprehensive review covers quantitative trait loci mapping, genome-wide association studies, key genes and functions, CRISPR-Cas applications, transcription factors, physiological responses, signaling pathways, offering a nuanced understanding of intricate mechanisms involved in maize drought tolerance.

A Comprehensive Analysis of Drought Stress Responses in Rice (Oryza sativa L.): Insights into Developmental Stage Variations from Germination to Grain Filling

Rice (Oryza sativa L.) is a critical staple food crop vulnerable to drought stress at key growth stages, namely the early seedling stage, vegetative phase, anthesis (reproductive stage), and grain ripening stage. The impact of drought stress on rice extends beyond mere water deficit, influencing a spectrum of morphological, physiological, biochemical, and molecular responses crucial for plant survival and productivity. This review synthesizes current understanding of rice responses to drought stress across its developmental stages, encompassing seed germination, seedling establishment, vegetative growth, reproductive development, and grain filling. Drought stress triggers multifaceted adaptations in rice, involving mechanisms such as escape, avoidance, tolerance, and recovery strategies to mitigate water scarcity effects. These responses are finely tuned across developmental stages, influencing traits like root architecture, stomatal conductance, photosynthetic efficiency, osmotic adjustment, and hormonal regulation. Understanding these responses is pivotal for enhancing rice resilience to drought, thereby safeguarding global food security and supporting the livelihoods of rice-dependent communities worldwide, particularly in regions like India where rice cultivation plays a crucial socioeconomic role. Challenges persist in deciphering the complex genetic and physiological networks underpinning drought responses in rice. Integrating omics approaches and advanced phenotyping techniques holds promise in unraveling these complexities and identifying genetic markers for drought tolerance. Furthermore, strategies such as breeding resilient cultivars and implementing agronomic practices tailored to specific growth stages are imperative for sustainable rice production under increasingly erratic climatic conditions. This review consolidates existing knowledge while highlighting gaps in current understanding, aiming to guide future research endeavors toward innovative solutions for enhancing rice drought resilience. By elucidating the intricate mechanisms governing rice responses to drought stress, this study contributes to the broader discourse on agricultural sustainability and climate change resilience in staple food crops.

NRC immune receptor networks show diversified hierarchical genetic architecture across plant lineages.

Plants' complex immune systems include nucleotide-binding domain and leucine-rich repeat-containing (NLR) proteins, which help recognize invading pathogens. In solanaceous plants, the NRC (NLR required for cell death) family includes helper NLRs that form a complex genetic network with multiple sensor NLRs to provide resistance against pathogens. However, the evolution and function of NRC networks outside solanaceous plants are currently unclear. Here, we conducted phylogenomic and macroevolutionary analyses comparing NLRs identified from different asterid lineages and found that NRC networks expanded significantly in most lamiids but not in Ericales and campanulids. Using transient expression assays in Nicotiana benthamiana, we showed that NRC networks are simple in Ericales and campanulids, but have high complexity in lamiids. Phylogenetic analyses grouped the NRC helper NLRs into three NRC0 subclades that are conserved, and several family-specific NRC subclades of lamiids that show signatures of diversifying selection. Functional analyses revealed that members of the NRC0 subclades are partially interchangeable, whereas family-specific NRC members in lamiids lack interchangeability. Our findings highlight the distinctive evolutionary patterns of the NRC networks in asterids and provide potential insights into transferring disease resistance across plant lineages.

A genome-wide association study reveals novel loci and candidate genes associated with plant height variation in Medicago sativa

BackgroundPlant height (PH) is an important agronomic trait influenced by a complex genetic network. However, the genetic basis for the variation in PH in Medicago sativa remains largely unknown. In this study, a comprehensive genome-wide association analysis was performed to identify genomic regions associated with PH using a diverse panel of 220 accessions of M. sativa worldwide.ResultsOur study identified eight novel single nucleotide polymorphisms (SNPs) significantly associated with PH evaluated in five environments, explaining 8.59–12.27% of the phenotypic variance. Among these SNPs, the favorable genotype of chr6__31716285 had a low frequency of 16.4%. Msa0882400, located proximal to this SNP, was annotated as phosphate transporter 3;1, and its role in regulating alfalfa PH was supported by transcriptome and candidate gene association analysis. In addition, 21 candidate genes were annotated within the associated regions that are involved in various biological processes related to plant growth and development.ConclusionsOur findings provide new molecular markers for marker-assisted selection in M. sativa breeding programs. Furthermore, this study enhances our understanding of the underlying genetic and molecular mechanisms governing PH variations in M. sativa.

'Organ'ising Floral Organ Development.

Flowers are plant structures characteristic of the phylum Angiosperms composed of organs thought to have emerged from homologous structures to leaves in order to specialize in a distinctive function: reproduction. Symmetric shapes, colours, and scents all play important functional roles in flower biology. The evolution of flower symmetry and the morphology of individual flower parts (sepals, petals, stamens, and carpels) has significantly contributed to the diversity of reproductive strategies across flowering plant species. This diversity facilitates attractiveness for pollination, protection of gametes, efficient fertilization, and seed production. Symmetry, the establishment of body axes, and fate determination are tightly linked. The complex genetic networks underlying the establishment of organ, tissue, and cellular identity, as well as the growth regulators acting across the body axes, are steadily being elucidated in the field. In this review, we summarise the wealth of research already at our fingertips to begin weaving together how separate processes involved in specifying organ identity within the flower may interact, providing a functional perspective on how identity determination and axial regulation may be coordinated to inform symmetrical floral organ structures.

The SEPALLATA-like CaSEP5 gene regulates flower sepal, pedicel, and fruit development in pepper (Capsicum annuum L.)

Flowers are reproductive plant organs that determine final fruit or seed yield. SEPALLATA-like MADS-box genes participate in floral determination and/or flower organ specification. Nevertheless, their molecular mechanisms in bell pepper have not yet been elucidated. In this study, we identified CaSEP5, which encodes a duplicated SEPALLATA-like MADS-box protein grouped in the FBP9/23-subclade. CaSEP5 genes were detected in all whorls of floral organs, and were relatively highly expressed in the sepals and petals. Subcellular localization revealed that CaSEP5 was in the nucleus. This finding aligns with transcription factor characteristics. The physical interactions of CaSEP5 with B-, C-, and other CaSEPs indicated that CaSEP5 act as glue to form protein complexes to regulate flower development by altering the hormones level and distribution. CaSEP5-silenced plants had elongated, leaf-like sepals, rigid, straight pedicels, reduced fruit size, altered expression patterns of other floral homeotic genes, and varied hormone levels. We proposed that CaSEP5 plays an important role in pepper flower and fruit development by means of a complex hormone and genetic network.

Machine learning analysis of RB-TnSeq fitness data predicts functional gene modules in Pseudomonas putida KT2440.

This study demonstrates a rapid, automated approach for elucidating functional modules within complex genetic networks. While Pseudomonas putida randomly barcoded transposon insertion sequencing data were used as a proof of concept, this approach is applicable to any organism with existing functional genomics data sets and may serve as a useful tool for many valuable applications, such as guiding metabolic engineering efforts in other microbes or understanding functional relationships between virulence-associated genes in pathogenic microbes. Furthermore, this work demonstrates that comparison of data obtained from independent component analysis of transcriptomics and gene fitness datasets can elucidate regulatory-functional relationships between genes, which may have utility in a variety of applications, such as metabolic modeling, strain engineering, or identification of antimicrobial drug targets.

GIGANTEA Unveiled: Exploring Its Diverse Roles and Mechanisms.

GIGANTEA (GI) is a conserved nuclear protein crucial for orchestrating the clock-associated feedback loop in the circadian system by integrating light input, modulating gating mechanisms, and regulating circadian clock resetting. It serves as a core component which transmits blue light signals for circadian rhythm resetting and overseeing floral initiation. Beyond circadian functions, GI influences various aspects of plant development (chlorophyll accumulation, hypocotyl elongation, stomatal opening, and anthocyanin metabolism). GI has also been implicated to play a pivotal role in response to stresses such as freezing, thermomorphogenic stresses, salinity, drought, and osmotic stresses. Positioned at the hub of complex genetic networks, GI interacts with hormonal signaling pathways like abscisic acid (ABA), gibberellin (GA), salicylic acid (SA), and brassinosteroids (BRs) at multiple regulatory levels. This intricate interplay enables GI to balance stress responses, promoting growth and flowering, and optimize plant productivity. This review delves into the multifaceted roles of GI, supported by genetic and molecular evidence, and recent insights into the dynamic interplay between flowering and stress responses, which enhance plants' adaptability to environmental challenges.

Genetic Network Design Automation with LOICA.

Genetic design automation (GDA) is the use of computer-aided design (CAD) in designing genetic networks. GDA tools are necessary to create more complex synthetic genetic networks in a high-throughput fashion. At the core of these tools is the abstraction of a hierarchy of standardized components. The components' input, output, and interactions must be captured and parametrized from relevant experimental data. Simulations of genetic networks should use those parameters and include the experimental context to be compared with the experimental results.This chapter introduces Logical Operators for Integrated Cell Algorithms (LOICA), a Python package used for designing, modeling, and characterizing genetic networks using a simple object-oriented design abstraction. LOICA represents different biological and experimental components as classes that interact to generate models. These models can be parametrized by direct connection to the Flapjack experimental data management platform to characterize abstracted components with experimental data. The models can be simulated using stochastic simulation algorithms or ordinary differential equations with varying noise levels. The simulated data can be managed and published using Flapjack alongside experimental data for comparison. LOICA genetic network designs can be represented as graphs and plotted as networks for visual inspection and serialized as Python objects or in the Synthetic Biology Open Language (SBOL) format for sharing and use in other designs.

Transcriptome Analysis of Macrophytes' Myriophyllum spicatum Response to Ammonium Nitrogen Stress Using the Whole Plant Individual.

Ammonium toxicity in macrophytes reduces growth and development due to a disrupted metabolism and high carbon requirements for internal ammonium detoxification. To provide more molecular support for ammonium detoxification in the above-ground and below-ground parts of Myriophyllum spicatum, we separated (using hermetic bags) the aqueous medium surrounding the below-ground from that surrounding the above-ground and explored the genes in these two regions. The results showed an upregulation of asparagine synthetase genes under high ammonium concentrations. Furthermore, the transcriptional down and/or upregulation of other genes involved in nitrogen metabolism, including glutamate dehydrogenase, ammonium transporter, and aspartate aminotransferase in above-ground and below-ground parts were crucial for ammonium homeostasis under high ammonium concentrations. The results suggest that, apart from the primary pathway and alternative pathway, the asparagine metabolic pathway plays a crucial role in ammonium detoxification in macrophytes. Therefore, the complex genetic regulatory network in M. spicatum contributes to its ammonium tolerance, and the above-ground part is the most important in ammonium detoxification. Nevertheless, there is a need to incorporate an open-field experimental setup for a conclusive picture of nitrogen dynamics, toxicity, and the molecular response of M. spicatum in the natural environment.

Physiological, Cytological, and Transcriptomic Analysis of Magnesium Protoporphyrin IX Methyltransferase Mutant Reveal Complex Genetic Regulatory Network Linking Chlorophyll Synthesis and Chloroplast Development in Rice.

Functional defects in key genes for chlorophyll synthesis usually cause abnormal chloroplast development, but the genetic regulatory network for these key genes in regulating chloroplast development is still unclear. Magnesium protoporphyrin IX methyltransferase (ChlM) is a key rate-limiting enzyme in the process of chlorophyll synthesis. Physiological analysis showed that the chlorophyll and carotenoid contents were significantly decreased in the chlm mutant. Transmission electron microscopy demonstrated that the chloroplasts of the chlm mutant were not well developed, with poor, loose, and indistinct thylakoid membranes. Hormone content analysis found that jasmonic acid, salicylic acid, and auxin accumulated in the mutant. A comparative transcriptome profiling identified 1534 differentially expressed genes (DEGs) between chlm and the wild type, including 876 up-regulated genes and 658 down-regulated genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed that these DEGs were highly involved in chlorophyll metabolism, chloroplast development, and photosynthesis. Protein-protein interaction network analysis found that protein translation played an essential role in the ChlM gene-regulated process. Specifically, 62 and 6 DEGs were annotated to regulate chlorophyll and carotenoid metabolism, respectively; 278 DEGs were predicted to be involved in regulating chloroplast development; 59 DEGs were found to regulate hormone regulatory pathways; 192 DEGs were annotated to regulate signal pathways; and 49 DEGs were putatively identified as transcription factors. Dozens of these genes have been well studied and reported to play essential roles in chlorophyll accumulation or chloroplast development, providing direct evidence for the reliability of the role of the identified DEGs. These findings suggest that chlorophyll synthesis and chloroplast development are actively regulated by the ChlM gene. And it is suggested that hormones, signal pathways, and transcription regulation were all involved in these regulation processes. The accuracy of transcriptome data was validated by quantitative real-time PCR (qRT-PCR) analysis. This study reveals a complex genetic regulatory network of the ChlM gene regulating chlorophyll synthesis and chloroplast development. The ChlM gene's role in retrograde signaling was discussed. Jasmonic acid, salicylic acid, or their derivatives in a certain unknown state were proposed as retrograde signaling molecules in one of the signaling pathways from the chloroplast to nucleus.

Plasmid Crosstalk in Cell-Free Expression Systems.

Although cell-free protein expression has been widely used for the synthesis of single proteins, cell-free synthetic biology has rapidly expanded to new, more complex applications. One such application is the prototyping or implementation of complex genetic networks involving the expression of multiple proteins at precise ratios, often from different plasmids. However, expression of multiple proteins from multiple plasmids may inadvertently result in unexpected, off-target changes to the levels of the proteins being expressed, a phenomenon termed plasmid crosstalk. Here, we show that the effects of plasmid crosstalk─even at the qualitative level of increases vs decreases in protein expression─depend on the concentration of plasmids in the reaction and the type of transcriptional machinery involved in the expression. This crosstalk can have a significant impact on genetic circuitry function and even interpretation of simple experimental results and thus should be taken into consideration during the development of cell-free applications.

Deciphering Millet Diversity: Proteomic Clusters and Phylogenetic Insights

Deciphering Millet Diversity: Proteomic Clusters and Phylogenetic Insights

A meta-QTL analysis highlights genomic hotspots associated with phosphorus use efficiency in rice (Oryza sativa L.).

Phosphorus use efficiency (PUE) is a complex trait, governed by many minor quantitative trait loci (QTLs) with small effects. Advances in molecular marker technology have led to the identification of QTLs underlying PUE. However, their practical use in breeding programs remains challenging due to the unstable effects in different genetic backgrounds and environments, interaction with soil status, and linkage drag. Here, we compiled PUE QTL information from 16 independent studies. A total of 192 QTLs were subjected to meta-QTL (MQTL) analysis and were projected into a high-density SNP consensus map. A total of 60 MQTLs, with significantly reduced number of initial QTLs and confidence intervals (CI), were identified across the rice genome. Candidate gene (CG) mining was carried out for the 38 MQTLs supported by multiple QTLs from at least two independent studies. Genes related to amino and organic acid transport and auxin response were found to be abundant in the MQTLs linked to PUE. CGs were cross validated using a root transcriptome database (RiceXPro) and haplotype analysis. This led to the identification of the eight CGs (OsARF8, OsSPX-MFS3, OsRING141, OsMIOX, HsfC2b, OsFER2, OsWRKY64, and OsYUCCA11) modulating PUE. Potential donors for superior PUE CG haplotypes were identified through haplotype analysis. The distribution of superior haplotypes varied among subspecies being mostly found in indica but were largely scarce in japonica. Our study offers an insight on the complex genetic networks that modulate PUE in rice. The MQTLs, CGs, and superior CG haplotypes identified in our study are useful in the combination of beneficial alleles for PUE in rice.

Input-to-state stability of stochastic Markovian jump genetic regulatory networks

The development of gene circuits in logic modules that start enormous output distributions with low signal-to-noise ratios is a difficult problem in engineering. As a result, the gene model depicts the transcription and translation of a single gene produced in the modification of noise in isolated logic modules. Our goal is to construct such networks with all types of connectivity. Further, the impacts of noise on further complex genetic networks have been investigated using stochastic gene models. Using this information as a foundation, our research investigates the input-to-state stability investigation for stochastic Markovian jump genetic regulatory networks with time-varying delay components. The goal of this article is to develop genetic networks with temporal delays, which are crucial for genetic regulation because slow biochemical processes like gene transcription and translation need time to occur. Additionally, the Markovian chain is essential for demonstrating how a system shifts from one mode to another with known transition probabilities. In the stochastic case, some complex systems with random disturbance will occur. Due to this significance the genetic regulatory network with stochastic case is applied to identify the complex behaviour among genes and proteins of the micro perspective. By establishing the Lyapunov functional with Ito’s and Dynkin’s formula, new stability conditions are derived and which is effectively solved by MATLAB toolbox. The efficiency of the suggested technique is demonstrated using a numerical example.

Noncoding RNA mutations in cancer.

Cancer is driven by both germline and somatic genetic changes. Efforts have been devoted to characterizing essential genetic variations in cancer initiation and development. Most attention has been given to mutations in protein-coding genes and associated regulatory elements such as promoters and enhancers. The development of sequencing technologies and in silico and experimental methods has allowed further exploration of cancer predisposition variants and important somatic mutations in noncoding RNAs, mainly for long noncoding RNAs and microRNAs. Association studies including GWAS have revealed hereditary variations including SNPs and indels in lncRNA or miRNA genes and regulatory regions. These mutations altered RNA secondary structures, expression levels, and target recognition and then conferred cancer predisposition to carriers. Whole-exome/genome sequencing comparing cancer and normal tissues has revealed important somatic mutations in noncoding RNA genes. Mutation hotspots and somatic copy number alterations have been identified in various tumor-associated noncoding RNAs. Increasing focus and effort have been devoted to studying the noncoding region of the genome. The complex genetic network of cancer initiation is being unveiled. This article is categorized under: RNA in Disease and Development > RNA in Disease.

Expression quantitative trait loci mapping identified PtrXB38 as a key hub gene in adventitious root development in Populus.

Plant establishment requires the formation and development of an extensive root system with architecture modulated by complex genetic networks. Here, we report the identification of the PtrXB38 gene as an expression quantitative trait loci (eQTL) hotspot, mapped using 390 leaf and 444 xylem Populus trichocarpa transcriptomes. Among predicted targets of this trans-eQTL were genes involved in plant hormone responses and root development. Overexpression of PtrXB38 in Populus led to significant increases in callusing and formation of both stem-born roots and base-born adventitious roots. Omics studies revealed that genes and proteins controlling auxin transport and signaling were involved in PtrXB38-mediated adventitious root formation. Protein-protein interaction assays indicated that PtrXB38 interacts with components of endosomal sorting complexes required for transport machinery, implying that PtrXB38-regulated root development may be mediated by regulating endocytosis pathway. Taken together, this work identified a crucial root development regulator and sheds light on the discovery of other plant developmental regulators through combining eQTL mapping and omics approaches.