A tug-of-war between the host and the pathogen generates strategic hotspots for the development of novel therapeutic interventions against infectious diseases

Single cell genomics based insights into the impact of cell-type specific microbial internalization on disease severity

Host-microbe interactions are complex and ever-changing, especially during infections, which can significantly impact human physiology in both health and disease by influencing metabolic and immune functions. Infections caused by pathogens such as bacteria, viruses, fungi, and parasites are the leading cause of global mortality. Microbes have evolved various immune evasion strategies to survive within their hosts, which presents a multifaceted challenge for detection. Intracellular microbes, in particular, target specific cell types for survival and replication and are influenced by factors such as functional roles, nutrient availability, immune evasion, and replication opportunities. Identifying intracellular microbes can be difficult because of the limitations of traditional culture-based methods. However, advancements in integrated host microbiome single-cell genomics and transcriptomics provide a promising basis for personalized treatment strategies. Understanding host-microbiota interactions at the cellular level may elucidate disease mechanisms and microbial pathogenesis, leading to targeted therapies. This article focuses on how intracellular microbes reside in specific cell types, modulating functions through persistence strategies to evade host immunity and prolong colonization. An improved understanding of the persistent intracellular microbe-induced differential disease outcomes can enhance diagnostics, therapeutics, and preventive measures.

From Prevention to Management: Understanding Postoperative Infections in Gynaecology

This narrative review examines the multifaceted realm of postoperative infections in gynaecology, addressing their significance, types, risk factors, prevention, management, and emerging trends. Postoperative infections, encompassing surgical site infections, urinary tract infections, and pelvic inflammatory disease, pose considerable challenges in patient care, warranting comprehensive exploration. Strategies for prevention include preoperative patient assessment, antimicrobial prophylaxis, and aseptic techniques. Intraoperative measures encompass infection control and instrument sterilization, while postoperative care involves wound management and early infection detection. Diagnostic tools, including blood tests, imaging, and microbiological cultures, aid in timely identification. Management strategies encompass antibiotic therapy, surgical interventions, supportive care, and addressing complications. The review underscores the necessity of personalized approaches, multidisciplinary collaboration, and innovative technologies in future infection management. It calls for ongoing research, heightened awareness, and meticulous care to minimize the impact of postoperative infections and optimize patient outcomes.

Rapid Escherichia coli Cloned DNA Detection in Serum Using an Electrical Double Layer-Gated Field-Effect Transistor-Based DNA Sensor

In this study, a rapid diagnosis platform was developed for the detection of Escherichia coli O157:H7. An electrical double layer (EDL)-gated field-effect transistor-based biosensor (BioFET) as a point-of-care testing device is demonstrated with its high sensitivity, portability, high selectivity, quick response, and ease of use. The specially designed ssDNA probe was immobilized on the extended gate electrode to bind the target complementary DNA segment of E. coli, resulting in a sharp drain current change within minutes. The limit of detection for target DNA is validated to a concentration of 1 fM in buffer solution and serum. Meanwhile, the results of a Kelvin probe force microscope were shown to have reduced surface potential of the DNA immobilized sensors before and after the cDNA detection, which is consistent with the decreased drain current of the BioFET. A 1.2 kb E. coli duplex DNA synthesized in plasmid was sonicated and detected in serum samples with the sensor array. Gel electrophoresis was used to confirm the efficiency of sonication by elucidating the length of DNA. Those results show that the EDL-gated BioFET system is a promising platform for rapid identification of pathogens for future clinical needs.

Play the plug: How bacteria modify recognition by host receptors?

The diverse microbial community that colonizes the gastrointestinal tract has remarkable effects on the host immune system and physiology resulting in homeostasis or disease. In both scenarios, the gut microbiota interacts with their host through ligand-receptor binding whereby the downstream signaling processes determine the outcome of the interaction as disease or the counteractive immune responses of the host. Despite several studies on microbe-host interactions and the mechanisms by which this intricate process happens, a comprehensive and updated inventory of known ligand-receptor interactions and their roles in disease is paramount. The ligands which originate as a result of microbial responses to the host environment contribute to either symbiotic or parasitic relationships. On the other hand, the host receptors counteract the ligand actions by mounting a neutral or an innate response. The varying degrees of polymorphic changes in the host receptors contribute to specificity of interaction with the microbial ligands. Additionally, pathogenic microbes manipulate host receptors with endogenous enzymes belonging to the effector protein family. This review focuses on the diversity and similarity in the gut microbiome-host interactions both in health and disease conditions. It thus establishes an overview that can help identify potential therapeutic targets in response to critically soaring antimicrobial resistance as juxtaposed to tardy antibiotic development research.

Evaluating complete surface-associated and secretory proteome of Leishmania donovani for discovering novel vaccines and diagnostic targets

The protozoa Leishmania donovani causes visceral leishmaniasis (kala-azar), the third most common vector-borne disease. The visceral organs, particularly the spleen, liver, and bone marrow, are affected by the disease. The lack of effective treatment regimens makes curing and eradicating the disease difficult. The availability of complete L. donovani genome/proteome data allows for the development of specific and efficient vaccine candidates using the reverse vaccinology method, while utilizing the unique sequential and structural features of potential antigenic proteins to induce protective T cell and B cell responses. Such shortlisted candidates may then be tested quickly for their efficacy in the laboratory and later in clinical settings. These antigens will also be useful for designing antigen-based next-generation sero-diagnostic assays. L. donovani's cell surface-associated proteins and secretory proteins are among the first interacting entities to be exposed to the host immune machinery. As a result, potential antigenic epitope peptides derived from these proteins could serve as competent vaccine components. We used a stepwise filtering-based in silico approach to identify the entire surface-associated and secretory proteome of L. donovani, which may provide rationally selected most exposed antigenic proteins. Our study identified 12 glycosylphosphatidylinositol-anchored proteins, 45 transmembrane helix-containing proteins, and 73 secretory proteins as potent antigens unique to L. donovani. In addition, we used immunoinformatics to identify B and T cell epitopes in them. Out of the shortlisted surface-associated and secretory proteome, 66 protein targets were found to have the most potential overlapping B cell and T cell epitopes (linear and conformational; MHC class I and MHC class II).

Engineered Cell Line Imaging Assay Differentiates Pathogenic from Non-Pathogenic Bacteria

Cell culture systems have greatly expanded our understanding of how bacterial pathogens target signaling pathways to manipulate the host and cause infection. Advances in genetic engineering have allowed for the creation of fluorescent protein readouts within signaling pathways, but these techniques have been underutilized in pathogen biology. Here, we genetically engineered a lung cell line with fluorescent reporters for extracellular signal-related kinase (ERK) and the downstream transcription factor FOS-related antigen 1 (Fra1) and evaluated signaling after inoculation with pathogenic and non-pathogenic bacteria. Cells were inoculated with 100 colony-forming units of Acinetobacter baylyi, Klebsiella pneumoniae, Pseudomonas aeruginosa, Streptococcus agalactiae, or Staphylococcus epidermidis and imaged in a multi-mode reader. The alamarBlue cell viability assay was used as a reference test and showed that pathogenic P. aeruginosa induced significant (p < 0.05) cell death after 8 h in both wild-type and engineered cell lines compared to non-pathogenic S. epidermidis. In engineered cells, we found that Fra1 signaling was disrupted in as little as 4 h after inoculation with bacterial pathogens compared to delayed disruption in signaling by non-pathogenic S. epidermidis. Overall, we demonstrate that low levels of pathogenic versus non-pathogenic bacteria can be rapidly and sensitively screened based on ERK-Fra1 signaling.

Statistical Modeling for the Prediction of Infectious Disease Dissemination With Special Reference to COVID-19 Spread

In this review, we have discussed the different statistical modeling and prediction techniques for various infectious diseases including the recent pandemic of COVID-19. The distribution fitting, time series modeling along with predictive monitoring approaches, and epidemiological modeling are illustrated. When the epidemiology data is sufficient to fit with the required sample size, the normal distribution in general or other theoretical distributions are fitted and the best-fitted distribution is chosen for the prediction of the spread of the disease. The infectious diseases develop over time and we have data on the single variable that is the number of infections that happened, therefore, time series models are fitted and the prediction is done based on the best-fitted model. Monitoring approaches may also be applied to time series models which could estimate the parameters more precisely. In epidemiological modeling, more biological parameters are incorporated in the models and the forecasting of the disease spread is carried out. We came up with, how to improve the existing modeling methods, the use of fuzzy variables, and detection of fraud in the available data. Ultimately, we have reviewed the results of recent statistical modeling efforts to predict the course of COVID-19 spread.

Computational Biology and Machine Learning Approaches to Understand Mechanistic Microbiome-Host Interactions

The microbiome, by virtue of its interactions with the host, is implicated in various host functions including its influence on nutrition and homeostasis. Many chronic diseases such as diabetes, cancer, inflammatory bowel diseases are characterized by a disruption of microbial communities in at least one biological niche/organ system. Various molecular mechanisms between microbial and host components such as proteins, RNAs, metabolites have recently been identified, thus filling many gaps in our understanding of how the microbiome modulates host processes. Concurrently, high-throughput technologies have enabled the profiling of heterogeneous datasets capturing community level changes in the microbiome as well as the host responses. However, due to limitations in parallel sampling and analytical procedures, big gaps still exist in terms of how the microbiome mechanistically influences host functions at a system and community level. In the past decade, computational biology and machine learning methodologies have been developed with the aim of filling the existing gaps. Due to the agnostic nature of the tools, they have been applied in diverse disease contexts to analyze and infer the interactions between the microbiome and host molecular components. Some of these approaches allow the identification and analysis of affected downstream host processes. Most of the tools statistically or mechanistically integrate different types of -omic and meta -omic datasets followed by functional/biological interpretation. In this review, we provide an overview of the landscape of computational approaches for investigating mechanistic interactions between individual microbes/microbiome and the host and the opportunities for basic and clinical research. These could include but are not limited to the development of activity- and mechanism-based biomarkers, uncovering mechanisms for therapeutic interventions and generating integrated signatures to stratify patients.

Insights into the Gryllus bimaculatus Immune-Related Transcriptomic Profiling to Combat Naturally Invading Pathogens

Natural pathogen pressure is an important factor that shapes the host immune defense mechanism. The current study primarily aimed to explore the molecular basis of the natural immune defense mechanism of a sporadic pest, Gryllus bimaculatus, during swarming by constructing cDNA libraries of the female mid-gut, male mid-gut, testes, and ovaries. The Illumina HiSeq platform generated an average of 7.9 G, 11.77 G, 10.07 G, and 10.07 G bases of outputs from the male mid-gut, female mid-gut, testes, and ovaries and libraries, respectively. The transcriptome of two-spotted field crickets was assembled into 233,172 UniGenes, which yielded approximately 163.58 million reads. On the other hand, there were 43,055 genes in common that were shared among all the biological samples. Gene Ontology analysis successfully annotated 492 immune-related genes, which comprised mainly Pattern Recognition Receptors (62 genes), Signal modulators (57 genes), Signal transduction (214 genes), Effectors (36 genes), and another immune-related 123 genes. In summary, the identified wide range of immune-related genes from G. bimaculatus indicates the existence of a sophisticated and specialized broad spectrum immune mechanism against invading pathogens, which provides, for the first time, insights into the molecular mechanism of disease resistance among two-spotted field crickets.

IFN- signalling regulates RAW 264.7 macrophage activation, cytokine production, and killing activity

Type I IFN holds a critical role in host defence, providing protection against pathogenic organisms through coordinating a pro-inflammatory response. Type I IFN provides additional protection through mitigating this inflammatory response, preventing immunopathology. Within the context of viral infections, type I IFN signalling commonly results in successful viral clearance. Conversely, during bacterial infections, the role of type I IFN is less predictable, leading to either detrimental or beneficial outcomes. The factors responsible for the variability in the role of type I IFN remain unclear. Here, we aimed to elucidate differences in the effect of type I IFN signalling on macrophage functioning in the context of TLR activation. Using RAW 264.7 macrophages, we observed the influence of type I IFN to be dependent on the type of TLR ligand, length of TLR exposure and the timing of IFN-β signalling. However, in all conditions, IFN-β increased the production of the anti-inflammatory cytokine IL-10. Examination of RAW 264.7 macrophage function showed type I IFN to induce an activated phenotype by up-regulating MHC II expression and enhancing killing activity. Our results support a context-dependent role for type I IFN in regulating RAW 264.7 macrophage activity.

An immunoinformatics approach for design and validation of multi-subunit vaccine against Cryptosporidium parvum

An immunoinformatics-based approach is explored for potential multi-subunit vaccine candidates against Cryptosporidium parvum. We performed protein structure based systematic methodology for the development of a proficient multi-subunit vaccine candidate against C. parvum based on their probability of antigenicity, allergenicity and transmembrane helices as the screening criteria. The best-screened epitopes like B-cell epitopes (BCL), Helper T-lymphocytes (HTL) and cytotoxic T- lymphocytes (CTL) were joined by using the appropriate linkers to intensify and develop the presentation and processing of the antigenic molecules. Modeller software was used to generate the best 3D model of the subunit protein. RAMPAGE and other web servers were employed for the validation of the modeled protein. Furthermore, the predicted modeled structure was docked with the two known receptors like TLR2 and TLR4 through ClusPro web server. Based on the docking score, the multi-subunit vaccine docked with TLR2 was subjected to energy minimization by molecular dynamics (MD) simulation to examine their stability within a solvent system. From the simulation study, we found that the residue Glu-107 of subunit vaccine formed a hydrogen bond interaction with Arg-299 of the TLR2 receptor throughout the time frame of the MD simulation. The overall results showed that the multi-subunit vaccine could be an efficient vaccine candidate against C. parvum.

Recent Trends in System-Scale Integrative Approaches for Discovering Protective Antigens Against Mycobacterial Pathogens

Mycobacterial infections are one of the deadliest infectious diseases still posing a major health burden worldwide. The battle against these pathogens needs to focus on novel approaches and key interventions. In recent times, availability of genome scale data has revolutionized the fields of computational biology and immunoproteomics. Here, we summarize the cutting-edge ‘omics’ technologies and innovative system scale strategies exploited to mine the available data. These may be targeted using high-throughput technologies to expedite the identification of novel antigenic candidates for the rational next generation vaccines and serodiagnostic development against mycobacterial pathogens for which traditional methods have been failing.

The Damage-Response Framework as a Tool for the Physician-Scientist to Understand the Pathogenesis of Infectious Diseases

The Damage-Response Framework (DRF) is a powerful tool to inform research in infectious diseases. It can integrate clinical observation with microbiology and immunology to incorporate the role of the host response into the outcome of microbial pathogenesis. Although the role that microbial factors may play in the pathogenesis of infectious diseases is well recognized, the DRF brings the indispensable role of the host response to the fore. For example, inflammation may induce microbial control, but it can also produce host damage. On the other hand, insufficient inflammation may fail to induce sufficient microbial control. Each scenario may lead to the diagnosis of an infectious disease. Given the central role that the host response plays in the pathogenesis of infectious diseases, new strategies for treatment need to consider the nature of the host response as well as microbial factors.

System-wide coordinates of higher order functions in host-pathogen environment upon Mycobacterium tuberculosis infection

Molecular signatures and their interactions behind the successful establishment of infection of Mycobacterium tuberculosis (Mtb) inside macrophage are largely unknown. In this work, we present an inter-system scale atlas of the gene expression signatures, their interactions and higher order gene functions of macrophage-Mtb environment at the time of infection. We have carried out large-scale meta-analysis of previously published gene expression microarray studies andhave identified a ranked list of differentially expressed genes and their higher order functions in intracellular Mtb as well as the infected macrophage. Comparative analysis of gene expression signatures of intracellular Mtb with the in vitro dormant Mtb at different hypoxic and oxidative stress conditions led to the identification of the large number of Mtb functional groups, namely operons, regulons and pathways that were common and unique to the intracellular environment and dormancy state. Some of the functions that are specific to intracellular Mtb are cholesterol degradation and biosynthesis of immunomodulatory phenolic compounds. The molecular signatures we have identified to be involved in adaptation to different stress conditions in macrophage environment may be critical for designing therapeutic interventions against tuberculosis. And, our approach may be broadly applicable for investigating other host-pathogen interactions.

Targeting calpains: A novel immunomodulatory approach for microbial infections

Calpains are a family of Ca²⁺ dependent cytosolic non-lysosomal proteases with well conserved cysteine-rich domains for enzymatic activity. Due to their functional dependency on Ca²⁺ concentrations, they are involved in various cellular processes that are regulated by intracellular ca²⁺ concentration (i.e. embryo development, cell development and migration, maintenance of cellular architecture and structure etc.). Calpains are widely studied proteases in mammalian (i.e. mouse and human) physiology and pathophysiology due to their ubiquitous presence. For example, these proteases have been found to be involved in various inflammatory disorders such as neurodegeneration, cancer, brain and myocardial ischemia and infarction, cataract and muscular dystrophies etc. Besides their role in these sterile inflammatory conditions, calpains have also been shown to regulate a wide range of infectious diseases (i.e. sepsis, tuberculosis, gonorrhoea and bacillary dysentery etc.). One of these regulatory mechanisms mediated by calpains (i.e. calpain 1 and 2) during microbial infections involves the regulation of innate immune response, inflammation and cell death. Thus, the major emphasis of this review is to highlight the importance of calpains in the pathogenesis of various microbial (i.e. bacterial, fungal and viral) diseases and the use of calpain modulators as potential immunomodulators in microbial infections.

Multifaceted impact of trichothecene metabolites on plant-microbe interactions and human health

Fungi present in rhizosphere produce trichothecene metabolites which are small in size and amphipathic in nature and some of them may cross cell membranes passively. Hypocreaceae family of rhizosphere fungi produce trichothecene molecules, however it is not a mandatory characteristic of all genera. Some of these molecules are also reported as growth adjuvant, while others are reported as deleterious for the plant growth. In this review, we are exploring the roles of these compounds during plant-microbe interactions. The three-way interaction among the plants, symbiotic microbial agents (fungi and bacteria), and the pathogenic microbes (bacteria, fungi) or multicellular pathogens like nematodes involving these compounds may only help us to understand better the complex processes happening in the microcosm of rhizosphere. These metabolites may further modulate the activity of different proteins involved in the cell signalling events of defence-related response in plants. That may induce the defence system against pathogens and growth promoting gene expression in plants, while in animal cells, these molecules have reported biochemical and pharmacological effects such as inducing oxidative stress, cell-cycle arrest and apoptosis, and may be involved in maintenance of membrane integrity. The biochemistry, chemical structures and specific functional group-mediated activity of these compounds have not been studied in details yet. Few of these molecules are also recently reported as novel anti-cancer agent against human chondrosarcoma cells.

A multi-subunit based, thermodynamically stable model vaccine using combined immunoinformatics and protein structure based approach

Immunizations with the conventional vaccines have failed to effectively inhibit the incidences and further dissemination of the infections. To address it, we have implemented protein structure based strategies to design an efficient multi-epitope subunit vaccine against Mycobacterium avium subsp. paratuberculosis (MAP). Previously reported immunodominant peptide epitope sequences from MAP1611 protein were conjugated together with a stretch of conserved amino acid residues of heparin-binding hemagglutinin, reported as a TLR4 agonist and was employed as an adjuvant to polarize the cellular responses toward host protective Th1 responses. These three types of component peptides were combined with the help of relevant linkers for efficient separation to improve and intensify the antigen processing and presentation. The primary structures of these multi peptides were 3-dimensional homology modeled to yield the final chimeric vaccine. Further, its conformational correctness and stability enhancement was assessed using molecular dynamics (MD) simulations. Finally, disulfide engineering in the most flexible regions of the molecule yielded three potential mutants, Y593C-E610C, Q631C-A634C and a double mutant Q631C-A634C/Y593C-E610C. The double mutant represents thermodynamically most stable version among them. It is potentially highly antigenic, soluble and non-allergen molecule interacting with the TLR receptor expressed on the immune cells. This vaccine contains both T-cell and several B-cell epitopes and an adjuvant which potentially possess protective cellular and humoral immune responses triggering properties. The presented vaccine strategy will be proven a promising pathogen specific candidate with wide therapeutic application against MAP which may be extended to other prevalent infections in future.

Sphingosine-1-phosphate signaling: unraveling its role as a drug target against infectious diseases

Sphingosine-1-phosphate (S1P) signaling is reported in variety of cell types, including immune, endothelial and cancerous cells. It is emerging as a crucial regulator of cellular processes, such as apoptosis, cell proliferation, migration, differentiation and so on. This signaling pathway is initiated by the intracellular production and secretion of S1P through a cascade of enzymatic reactions. Binding of S1P to different S1P receptors (S1PRs) activates different downstream signaling pathways that regulate the cellular functions differentially depending upon the cell type. An accumulating body of evidence suggests that S1P metabolism and signaling is often impaired during infectious diseases; thus, its manipulation might be helpful in the treatment of such diseases. In this review, we summarize recent advances in our understanding of the S1P signaling pathway and its candidature as a novel drug target against infectious diseases.