Identification of biomarkers for the accurate and sensitive diagnosis of three bacterial pneumonia pathogens using in silico approaches

Fluorescent and electrochemical detection of nuclease activity associated with Streptococcus pneumoniae using specific oligonucleotide probes

Streptococcus pneumoniae (S. pneumoniae) represents a significant pathogenic threat, often responsible for community-acquired pneumonia with potentially life-threatening consequences if left untreated. This underscores the pressing clinical need for rapid and accurate detection of this harmful bacteria. In this study, we report the screening and discovery of a novel biomarker for S. pneumoniae detection. We used S. pneumoniae nucleases as biomarker and we have identified a specific oligonucleotide that works as substrate. This biomarker relies on a specific nuclease activity found on the bacterial membrane, forming the basis for the development of both fluorescence and electrochemical biosensors. We observed an exceptionally high sensitivity in the performance of the electrochemical biosensor, detecting as low as 102 CFU mL-1, whereas the fluorescence sensor demonstrated comparatively lower efficiency, with a detection limit of 106 CFU mL-1. Moreover, the specificity studies have demonstrated the biosensors' remarkable capacity to identify S. pneumoniae from other pathogenic bacteria. Significantly, both biosensors have demonstrated the ability to identify S. pneumoniae cultured from clinical samples, providing compelling evidence of the potential clinical utility of this innovative detection system.

Recent Advances in Electrochemical Biosensors Targeting Stress Markers

INTRODUCTION

When the body experiences a change in its internal environment due to factors such as mood (euphoria, stress) and illness, it releases biomarkers in large quantities. These biomarkers are used for detecting a disease at its early stages. This involves the detection of insufficient quantities of biocomponents, which can be done by using nanomaterials, conventional materials, and biotechnology; thus, scientists can increase the sensitivity of electrochemical sensors. According to studies conducted in this area, electrochemical sensors have shown promise as a diagnostic tool due to their ability to identify and pinpoint illness biomarkers. The present review article was compiled to gather the latest information on electrochemical biosensors targeting stress markers.

MATERIALS AND METHODS

The authors searched scholarly databases like ScienceDirect, Pubmed, Medline, and Scopus for information on electrochemical biosensors targeting stress markers.

RESULTS

In this article, we looked at the recent developments in electrochemical sensors for stress monitoring. Because of advances in nanomaterial and biomolecule processes, electrochemical biosensors have been developed with the sensitivity to detect several biomarkers in real-time in therapeutically relevant materials.

CONCLUSION

This biomarker sensor strategy can analyze various biofluids (sweat, plasma, urine, and saliva).

Extracellular vesicles in bacterial and fungal diseases - Pathogenesis to diagnostic biomarkers

Intercellular communication among microbes plays an important role in disease exacerbation. Recent advances have described small vesicles, termed as "extracellular vesicles" (EVs), previously disregarded as "cellular dust" to be vital in the intracellular and intercellular communication in host-microbe interactions. These signals have been known to initiate host damage and transfer of a variety of cargo including proteins, lipid particles, DNA, mRNA, and miRNAs. Microbial EVs, referred to generally as "membrane vesicles" (MVs), play a key role in disease exacerbation suggesting their importance in pathogenicity. Host EVs help coordinate antimicrobial responses and prime the immune cells for pathogen attack. Hence EVs with their central role in microbe-host communication, may serve as important diagnostic biomarkers of microbial pathogenesis. In this review, we summarize current research regarding the roles of EVs as markers of microbial pathogenesis with specific focus on their interaction with host immune defence and their potential as diagnostic biomarkers in disease conditions.

Detection, Diagnosis, and Preventive Management of the Bacterial Plant Pathogen Pseudomonas syringae

Plant diseases caused by the pathogen Pseudomonas syringae are serious problems for various plant species worldwide. Accurate detection and diagnosis of P. syringae infections are critical for the effective management of these plant diseases. In this review, we summarize the current methods for the detection and diagnosis of P. syringae, including traditional techniques such as culture isolation and microscopy, and relatively newer techniques such as PCR and ELISA. It should be noted that each method has its advantages and disadvantages, and the choice of each method depends on the specific requirements, resources of each laboratory, and field settings. We also discuss the future trends in this field, such as the need for more sensitive and specific methods to detect the pathogens at low concentrations and the methods that can be used to diagnose P. syringae infections that are co-existing with other pathogens. Modern technologies such as genomics and proteomics could lead to the development of new methods of highly accurate detection and diagnosis based on the analysis of genetic and protein markers of the pathogens. Furthermore, using machine learning algorithms to analyze large data sets could yield new insights into the biology of P. syringae and novel diagnostic strategies. This review could enhance our understanding of P. syringae and help foster the development of more effective management techniques of the diseases caused by related pathogens.

Assessment of Urinary Biomarkers for Infectious Diseases Using Lateral Flow Assays: A Comprehensive Overview

Screening of biomarkers is a powerful approach for providing a holistic view of the disease spectrum and facilitating the diagnosis and prognosis of the state of infectious diseases. Unaffected by the homeostasis mechanism in the human body, urine accommodates systemic changes and reflects the pathophysiological condition of an individual. Easy availability in large volumes and non-invasive sample collection have rendered urine an ideal source of biomarkers for various diseases. Infectious diseases may be communicable, and therefore early diagnosis and treatment are of immense importance. Current diagnostic approaches preclude the timely identification of clinical conditions and also lack portability. Point-of-care (POC) testing solutions have gained attention as alternative diagnostic measures due to their ability to provide rapid and on-site results. Lateral flow assays (LFAs) are the mainstay in POC device development and have attracted interest owing to their potential to provide instantaneous results in resource-limited settings. The discovery and optimization of a definitive biomarker can render POC testing an excellent platform, thus impacting unwarranted antibiotic administration and preventing the spread of infectious diseases. This Review summarizes the importance of urine as an emerging biological fluid in infectious disease research and diagnosis in clinical settings. We review the academic research related to LFAs. Further, we also describe commercial POC devices based on the identification of urinary biomarkers as diagnostic targets for infectious diseases. We also discuss the future use of LFAs in developing more effective POC tests for urinary biomarkers of various infections.

In silico discovery of biomarkers for the accurate and sensitive detection of Fusarium solani

Fusarium solani is worrisome because it severely threatens the agricultural productivity of certain crops such as tomatoes and peas, causing the general decline, wilting, and root necrosis. It has also been implicated in the infection of the human eye cornea. It is believed that early detection of the fungus could save these crops from the destructive activities of the fungus through early biocontrol measures. Therefore, the present work aimed to build a sensitive model of novel anti-Fusarium solani antimicrobial peptides (AMPs) against the fungal cutinase 1 (CUT1) protein for early, sensitive and accurate detection. Fusarium solani CUT1 receptor protein 2D secondary structure, model validation, and functional motifs were predicted. Subsequently, anti-Fusarium solani AMPs were retrieved, and the HMMER in silico algorithm was used to construct a model of the AMPs. After their structure predictions, the interaction analysis was analyzed for the Fusarium solani CUT1 protein and the generated AMPs. The putative anti-Fusarium solani AMPs bound the CUT1 protein very tightly, with OOB4 having the highest binding energy potential for HDock. The pyDockWeb generated high electrostatic, desolvation, and low van der Waals energies for all the AMPs against CUT1 protein, with OOB1 having the most significant interaction. The results suggested the utilization of AMPs for the timely intervention, control, and management of these crops, as mentioned earlier, to improve their agricultural productivity and reduce their economic loss and the use of HMMER for constructing models for disease detection.

Analytical Studies of Antimicrobial Peptides as Diagnostic Biomarkers for the Detection of Bacterial and Viral Pneumonia

Pneumonia remains one of the leading causes of infectious mortality and significant economic losses among our growing population. The lack of specific biomarkers for correct and timely diagnosis to detect patients' status is a bane towards initiating a proper treatment plan for the disease; thus, current biomarkers cannot distinguish between pneumonia and other associated conditions such as atherosclerotic plaques and human immunodeficiency virus (HIV). Antimicrobial peptides (AMPs) are potential candidates for detecting numerous illnesses due to their compensatory roles as theranostic molecules. This research sought to generate specific data for parental AMPs to identify viral and bacterial pneumonia pathogens using in silico technology. The parental antimicrobial peptides (AMPs) used in this work were AMPs discovered in our previous in silico analyses using the HMMER algorithm, which were used to generate derivative (mutated) AMPs that would bind with greater affinity, in order to detect the bacterial and viral receptors using an in silico site-directed mutagenesis approach. These AMPs' 3D structures were subsequently predicted and docked against receptor proteins. The result shows putative AMPs with the potential capacity to detect pneumonia caused by these pathogens through their binding precision with high sensitivity, accuracy, and specificity for possible use in point-of-care diagnosis. These peptides' tendency to detect receptor proteins of viral and bacterial pneumonia with precision justifies their use for differential diagnostics, in an attempt to reduce the problems of indiscriminate overuse, toxicity due to the wrong prescription, bacterial resistance, and the scarcity and high cost of existing pneumonia antibiotics.

Building HMM and molecular docking analysis for the sensitive detection of anti-viral pneumonia antimicrobial peptides (AMPs)

Pneumonia is the main reason for mortality among children under five years, causing 1.6 million deaths every year; late research has exhibited that mortality is increasing in the elderly. A few biomarkers used for its diagnosis need specificity and precision, as they are related to different infections, for example, pulmonary tuberculosis and Human Immunodeficiency Virus. There is a quest for new biomarkers worldwide to diagnose the disease to defeat these previously mentioned constraints. Antimicrobial peptides (AMPs) are promising indicative specialists against infection. This research work used AMPs as biomarkers to detect viral pneumonia pathogens, for example, Respiratory syncytial virus, Influenza A and B viruses utilizing in silico technologies, such as Hidden Markov Model (HMMER). HMMER was used to distinguish putative anti-viral pneumonia AMPs against the recognized receptor proteins of Respiratory syncytial virus, Influenza A, and B viruses. The physicochemical parameters of these putative AMPs were analyzed, and their 3-D structures were determined utilizing I-TASSER. Molecular docking interaction of these AMPs against the recognized viral pneumonia proteins was carried out using the PATCHDOCK and HDock servers. The results demonstrated 27 anti-viral AMPs ranked based on their E values with significant physicochemical parameters in similarity with known experimentally approved AMPs. The AMPs additionally had a high anticipated binding potential to the pneumonia receptors of these microorganisms sensitively. The tendency of the putative anti-viral AMPs to bind pneumonia proteins showed that they would be promising applicant biomarkers to identify these viral microorganisms in the point-of-care (POC) pneumonia diagnostics. The high precision observed for the AMPs legitimizes HMM's utilization in the disease diagnostics' discovery process.

Biomedical Relevance of Novel Anticancer Peptides in the Sensitive Treatment of Cancer

The global increase in cancer mortality and economic losses necessitates the cautious quest for therapeutic agents with compensatory advantages over conventional therapies. Anticancer peptides (ACPs) are a subset of host defense peptides, also known as antimicrobial peptides, which have emerged as therapeutic and diagnostic candidates due to several compensatory advantages over the non-specificity of the current treatment regimens. This review aimed to highlight the ravaging incidence of cancer, the use of ACPs in cancer treatment with their mechanisms, ACP discovery and delivery methods, and the limitations for their use. This would create awareness for identifying more ACPs with better specificity, accuracy and sensitivity towards the disease. It would also promote their efficacious utilization in biotechnology, medical sciences and molecular biology to ease the severity of the disease and enable the patients living with these conditions to develop an accommodating lifestyle.

PR-1-Like Protein as a Potential Target for the Identification of Fusarium oxysporum: An In Silico Approach

Fusarium oxysporum remains one of the leading causes of economic losses and poor crop yields; its detection is strained due to its presentation in various morphological and physiological forms. This research work sought to identify novel biomarkers for the detection of Fusarium oxysporum using in silico approaches. Experimentally validated anti-Fusarium oxysporum antimicrobial peptides (AMPs) were used to construct a profile against Fusarium oxysporum. The performance and physicochemical parameters of these peptides were predicted. The gene for the Fusarium oxysporum receptor protein PR-1-like Protein, Fpr1, was identified and translated. The resulting protein model from the translation was then validated. The anti-Fusarium oxysporum AMPs and Fusarium oxysporum receptor protein 3-D structures were characterized, and their docking interaction analyses were carried out. The HMMER in silico tool identified novel anti-Fusarium oxysporum antimicrobial peptides with good performance in terms of accuracy, sensitivity, and specificity. These AMPs also displayed good physicochemical properties and bound with greater affinity to Fusarium oxysporum protein receptor PR-1-like Protein. The tendency of these AMPs to precisely detect Fusarium oxysporum PR-1-like Protein, Fpr1, would justify their use for the identification of the fungus. This study would enhance and facilitate the identification of Fusarium oxysporum to reduce problems associated with poor crop yield, economic losses, and decreased nutritional values of plants to keep up with the growing population.