Introduction: Thermus thermophilus is a thermophilic bacterium known for its resilience in extreme environments. Investigating its transcriptomic responses to environmental stresses can uncover critical adaptive mechanisms.

Materials and Methods: This study analyzed transcriptomic data from 10 microarray datasets, including 63 samples (36 stress-exposed and 27 controls). Stress conditions included copper, cold, zinc, iron, heat, salt, H₂O₂, tetracycline, diamide, and alkylation. Differentially expressed genes (DEGs) were identified through meta-analysis, followed by Gene Ontology (GO) enrichment analysis. Weighted gene co-expression network analysis (WGCNA) was employed to detect stress-associated gene modules. Machine learning approaches—decision tree, logistic regression, random forest, adaptive boosting, SVM-RFE, and XGBoost—were used to prioritize key genes.

Results: Meta-analysis revealed 54 upregulated and 196 downregulated genes under stress. GO analysis highlighted significant enrichment in ion transport, localization processes, and transmembrane transporter activity. WGCNA identified two stress-related modules, cyan and lightcyan. SVM-RFE and XGBoost outperformed other machine learning models with superior accuracy, precision, recall, and F1-scores. TTHA0798 emerged as a hub gene consistently identified across machine learning and DEG/WGCNA analyses.

Conclusions: This study provides a comprehensive analysis of the stress responses of T. thermophilus, identifying TTHA0798 as a key hub gene. The integration of transcriptomic data, co-expression analysis, and machine learning offers valuable insights into the adaptive mechanisms of this extremophile, paving the way for further functional studies. 

Background  Cyanobacteria, particularly Synechocystis sp. PCC 6803, serve as model organisms for studying acclimation strategies that enable adaptation to various environmental stresses. Understanding the molecular mechanisms underlying these adaptations provides insight into how cells adjust gene expression in response to challenging conditions.

Objective  To analyze the transcriptome data of Synechocystis sp. PCC 6803 under light, salinity, and iron stress conditions and to identify hub genes potentially involved in stress response, specifically comparing the findings with Geminocystis sp. NIES-3708.

Methods  A comprehensive bioinformatics approach was applied, integrating meta-analysis, weighted gene co-expression network analysis (WGCNA), and a Random Forest (RF) machine learning algorithm. These approaches underscore the robustness of our findings, allowing for a more nuanced understanding of gene interactions and their functional relevance in stress responses. This methodology was used to identify key hub genes in Synechocystis sp. PCC 6803 that may have conserved roles in Geminocystis sp. NIES-3708. A total of four potential hub genes, including slr1392, slr1484, sll1549, and sll1863, were identified. Among these, only sll1549 had a homolog (GM3708_2556) with 71% sequence similarity and 70% query coverage in Geminocystis sp. NIES-3708. The expression of GM3708_2556 was further evaluated under nitrate, salt, and combined salinity-nitrate stress conditions using RT-qPCR.

Results  Transcript levels of GM3708_2556 increased significantly under salt stress (3.35-fold, p-value < 0.05) and combined salinity-nitrate stress (2.24-fold, p-value < 0.05) compared to control conditions, while no significant change was observed under nitrate stress alone. These results suggest that GM3708_2556 may play a crucial role in the organism’s response to salt stress, with potential interactions in nitrate metabolism.

Conclusion  This study highlights the gene GM3708_2556 as a significant factor in salt stress response, with implications for conserved functional roles across cyanobacterial species. Furthermore, the findings have potential relevance to biotechnology, particularly in engineering stress-resistant cyanobacterial strains for applications in sustainable agriculture and bioenergy production.

Bacteria are constantly exposed to diverse environmental stresses, necessitating complex adaptive mechanisms for survival. Thermus thermophilus, a thermophilic extremophile, serves as an excellent model for investigating these responses due to its remarkable resilience to harsh conditions. Recent advances in artificial intelligence, particularly in machine learning, have transformed the identification of novel stress-responsive biomarkers. In this study, we analyzed transcriptomic data from 65 T. thermophilus HB8 samples subjected to various abiotic stresses to identify key genes involved in stress adaptation. We applied a suite of supervised machine learning algorithms to classify samples and prioritize informative features. Among the tested models, Extreme Gradient Boosting (XGBoost) and Random Forest (RF) achieved the highest classification performance, with XGBoost attaining perfect discrimination between stressed and control samples (AUC = 1.00) and RF closely following (AUC = 0.99). Feature importance analysis consistently identified three candidate genes: TTHA0029, TTHA1720, and TTHA1359. Functional validation using RT-qPCR confirmed the significant upregulation of TTHA0029 and TTHA1720 under salt and hydrogen peroxide stress, suggesting roles in redox regulation and ionic homeostasis. Phylogenetic analysis further revealed the specificity of these genes to the Thermus genus. Overall, our findings highlight central molecular players in stress tolerance in T. thermophilus and demonstrate the utility of machine learning in biomarker discovery. The identified genes, TTHA0029 and TTHA1720, may serve as promising targets for genetic engineering to improve stress resilience in both crops and industrially relevant microorganisms.

Transmission of Zika virus (ZIKV) has been reported in 92 countries and the geographical spread of invasive virus-borne vectors has increased in recent years. Arboviruses naturally survive between vertebrate hosts and arthropod vectors. Transmission success requires the mosquito to feed on viraemic hosts. There is little specific understanding of factors that may promote ZIKV transmission-success. Here we show that mosquito host-seeking behaviour is impacted by viral infection of the vertebrae host and may be essential for the effective transmission of arboviruses like ZIKV. Human skin fibroblasts produce a variety of metabolites, and we show that ZIKV immediately alters gene/protein expression patterns in infected-dermal fibroblasts, altering their metabolism to increase the release of mosquito-attractive volatile organic compounds (VOCs), which improves its transmission success. We demonstrate that at the invasion stage, ZIKV differentially altered the emission of VOCs by significantly increasing or decreasing their amounts, while at the transmission stage of the virus, all VOCs are significantly increased. The findings are complemented by an extensive meta-proteome analysis. Overall, we demonstrate a multifaceted role of virus-host interaction and shed light on how arboviruses may influence the behaviour of their vectors as an evolved means of improving transmission-success.

Cyanobacteria have developed acclimation strategies to adapt to harsh environments, making them a model organism. Understanding the molecular mechanisms of tolerance to abiotic stresses can help elucidate how cells change their gene expression patterns in response to stress. Recent advances in sequencing techniques and bioinformatics analysis methods have led to the discovery of many genes involved in stress response in organisms. The Synechocystis sp. PCC 6803 is a suitable microorganism for studying transcriptome response under environmental stress. Therefore, for the first time, we employed two effective feature selection techniques namely and support vector machine recursive feature elimination (SVM-RFE) and LASSO (Least Absolute Shrinkage Selector Operator) to pinpoint the crucial genes responsive to environmental stresses in Synechocystis sp. PCC 6803. We applied these algorithms of machine learning to analyze the transcriptomic data of Synechocystis sp. PCC 6803 under distinct conditions, encompassing light, salt and iron stress conditions. Seven candidate genes namely sll1862, slr0650, sll0760, slr0091, ssl3044, slr1285, and slr1687 were selected by both LASSO and SVM-RFE algorithms. RNA-seq analysis was performed to validate the efficiency of our feature selection approach in selecting the most important genes. The RNA-seq analysis revealed significantly high expression for five genes namely sll1862, slr1687, ssl3044, slr1285, and slr0650 under ion stress condition. Among these five genes, ssl3044 and slr0650 could be introduced as new potential candidate genes for further confirmatory genetic studies, to determine their roles in their response to abiotic stresses.

Deaths from malaria remain staggering despite global support that drives research into new territories. One major gap is our understanding of the sexual biological aspects of the male mosquito, which maintain the vector population solidity. Although Anopheles funestus s.s. is an extremely efficient African vector, little is known about the network between its sexual physiology and gene expression. The Culicidae male’s sexual maturity involves a suite of physiological changes, such as genitalia rotation that is necessary for successful mating to occur. We show that mating success is guided by genes and physiological plasticity. Transcriptome analysis between newly emerged males (immature) versus males with rotating genitalia (maturing) provides insight into possible molecular mechanisms regulating male sexual behaviour. Putative transcripts that were associated with male sexual maturation were identified and validated. The discovery of the functions of these transcripts could lead to identifying potential targets for innovative vector control interventions, and mosquito population suppression.

The coordinating role of nuclear factor erythroid-2-related factor 2 (Nrf2) in cellular function is undeniable. Evidence indicates that this transcription factor exerts massive regulatory functions in multiple signaling pathways concerning redox homeostasis and xenobiotics, macromolecules, and iron metabolism. Being the master regulator of antioxidant system, Nrf2 controls cellular fate, influencing cell proliferation, differentiation, apoptosis, resistance to therapy, and senescence processes, as well as infection disease success. Because Nrf2 is the key coordinator of cell defence mechanisms, dysregulation of its signaling has been associated with carcinogenic phenomena and infectious and age-related diseases. Deregulation of this cytoprotective system may also interfere with immune response. Oxidative burst, one of the main microbicidal mechanisms, could be impaired during the initial phagocytosis of pathogens, which could lead to the successful establishment of infection and promote susceptibility to infectious diseases. There is still a knowledge gap to fill regarding the molecular mechanisms by which Nrf2 orchestrates such complex networks involving multiple pathways. This review describes the role of Nrf2 in non-pathogenic and pathogenic cells.

Malaria inflicts the highest rate of morbidity and mortality among the vector-borne diseases. The dramatic bottleneck of parasite numbers that occurs in the gut of the obligatory mosquito vector provides a promising target for novel control strategies. Using single-cell transcriptomics, we analyzed Plasmodium falciparum development in the mosquito gut, from unfertilized female gametes through the first 20 h after blood feeding, including the zygote and ookinete stages. This study revealed the temporal gene expression of the ApiAP2 family of transcription factors and of parasite stress genes in response to the harsh environment of the mosquito midgut. Further, employing structural protein prediction analyses, we found several upregulated genes predicted to encode intrinsically disordered proteins (IDPs), a category of proteins known for their importance in regulation of transcription, translation, and protein-protein interactions. IDPs are known for their antigenic properties and may serve as suitable targets for antibody- or peptide-based transmission suppression strategies. In total, this study uncovers the P. falciparum transcriptome from early to late parasite development in the mosquito midgut, inside its natural vector, which provides an important resource for future malaria transmission-blocking initiatives.

Malaria parasites can affect vector-related behaviours, increasing transmission success. Using Anopheles gambiae and Plasmodium falciparum, we consider the effect of interaction between infection stage and vector age on diel locomotion in response to human odour and the expression of antennal chemosensory genes. We identified age-dependent behavioural diel compartmentalisation by uninfected females post-blood meal. Infection disrupts overall and diel activity patterns compared with age-matched controls. In this study, mosquitoes carrying transmissible sporozoites were more active, shifting activity periods which corresponded with human host availability, in response to human odour. Older, uninfected, blood-fed females displayed reduced activity during their peak host-seeking period in response to human odour. Age- and infection stage-specific changes in odour-mediated locomotion coincide with altered transcript abundance of select chemosensory genes suggesting a possible molecular mechanism regulating the behaviour. We hypothesize that vector-related behaviours of female mosquitoes are altered by infection stage and further modulated by the age post-blood meal of the vector. Findings may have important implications for malaria transmission and disease dynamics.

In eco-evolutionary studies of parasite-host interactions, virulence is defined as a reduction in host fitness as a result of infection relative to an uninfected host. Pathogen virulence may either promote parasite transmission, when correlated with higher parasite replication rate, or decrease the transmission rate if the pathogen quickly kills the host. This evolutionary mechanism, referred to as 'trade-off' theory, proposes that pathogen virulence evolves towards a level that most benefits the transmission. It has been generally predicted that pathogens evolve towards low virulence in their insect vectors, mainly due to the high dependence of parasite transmission on their vector survival. Therefore, the degree of virulence which malaria parasites impose on mosquito vectors may depend on several external and internal factors. Here, we review briefly (i) the role of mosquito in parasite development, with a particular focus on mosquito midgut as the battleground between Plasmodium and the mosquito host. We aim to point out (ii) the histology of the mosquito midgut epithelium and its role in host defence against parasite's countermeasures in the three main battle sites, namely (a) the lumen (microbiota and biochemical environment), (b) the peritrophic membrane (physical barrier) and (c) the tubular epithelium including the basal membrane (physical and biochemical barrier). Lastly, (iii) we describe the impact which malaria parasite and its virulence factors have on mosquito fitness.