Label-free quantitative proteomic analysis reveals potential biomarkers for early healing in cutaneous leishmaniasis

Plasma metabolomics and proteomics reveal novel molecular insights and biomarker panel for cholelithiasis

BACKGROUND

Cholelithiasis is a gastrointestinal disease that is associated with the highest socioeconomic cost. A diagnosis of cholelithiasis based on clinical features is significantly limited, and direct molecular insights into cholelithiasis and the relationship between cholelithiasis and clinical biochemical parameters are unclear.

OBJECTIVES

Uncovering direct molecular insights into cholelithiasis and the relationship between cholelithiasis and clinical biochemical parameters. Identifying sensitive and specific biomarkers for this disease.

METHODS

Parallel metabolomic and proteomic analyses of plasma from cholelithiasis patients (CPs) and healthy control individuals (HCs) without cholelithiasis were performed using ultrahigh-performance liquid chromatography-tandem mass spectrometry. A multimodule coexpression network analysis and integrated machine learning methods, including least absolute shrinkage and selection operator, random forest, and support vector machine, were used for bioinformatic analyses. An independent cohort and the cross-validation of the combination of two cohorts were used to evaluate the diagnostic performance of the panel.

RESULTS

Arachidonic acid metabolism was significantly different between the CP and HC groups. Glyceraldehyde-3-phosphate dehydrogenase, actin beta, phosphoglycerate mutase 1, Enolase 1, Myeloperoxidase, and actin alpha 1 were identified as potential proteins related to cholelithiasis. The correlation between the merged modules and clinical biochemical tests was calculated. A diagnostic panel composed of four candidate biomarkers, including 3-oxotetradecanoic acid, 12-hydroxydodecanoic acid, hemoglobin subunit delta (HBD), and fibrinogen beta chain (FGB), was proposed based on three modules that were significantly associated with cholelithiasis. The classification according to the diagnostic panel detected CPs with an area under the curve (AUC) of 0.955. External validation in an independent cohort resulted in similar accuracy (AUC=0.995).

CONCLUSIONS

This study provided some direct molecular insights into cholelithiasis by showing the differences in plasma metabolic and protein profiles between CPs and HCs and presented a potential biomarker panel with two metabolites (3-oxotetradecanoic acid, 12-hydroxydodecanoic acid) and two proteins (HBD, FGB) for predicting cholelithiasis. We also explored the potential correlation of clinical biochemical parameters with combined modules. These findings may provide some reference for the diagnosis of cholelithiasis in clinical practice.

Characterization and Proteomic Analysis of Plasma EVs Recovered from Healthy and Diseased Dogs with Canine Leishmaniosis

Dogs are highly valued companions and work animals that are susceptible to many life-threatening conditions such as canine leishmaniosis (CanL). Plasma-derived extracellular vesicles (EVs), exploited extensively in biomarker discovery, constitute a mostly untapped resource in veterinary sciences. Thus, the definition of proteins associated with plasma EVs recovered from healthy and diseased dogs with a relevant pathogen would be important for biomarker development. For this, we recovered, using size-exclusion chromatography (SEC), EVs from 19 healthy and 20 CanL dogs’ plasma and performed proteomic analysis by LC-MS/MS to define their core proteomic composition and search for CanL-associated alterations. EVs-specific markers were identified in all preparations and also non-EVs proteins. Some EVs markers such as CD82 were specific to the healthy animals, while others, such as the Integrin beta 3 were identified in most samples. The EVs-enriched preparations allowed the identification of 529 canine proteins that were identified in both groups, while 465 and 154 were only identified in healthy or CanL samples, respectively. A GO enrichment analysis revealed few CanL-specific terms. Leishmania spp. protein identifications were also found, although with only one unique peptide. Ultimately, CanL-associated proteins of interest were identified and a core proteome was revealed that will be available for intra- and inter-species comparisons.

Omics Approaches in Drug Development against Leishmaniasis: Current Scenario and Future Prospects

Leishmaniasis is a zoonotic disease transmitted in humans by the bite of Leishmania-infected phlebotomine sandflies. Each year approximately 58,500 cases of leishmaniasis are diagnosed across the globe, with a mortality rate of nearly seven percent. There are over 20 parasitic strains of Leishmania which are known to cause distinct types of leishmaniasis and pose an endemic threat to humans worldwide. Therefore, it is crucial to develop potential medications and vaccines to combat leishmaniasis. However, the task of developing therapeutic solutions is challenging due to Leishmania's digenetic lifecycle. The challenge is further intensified by cases of resistance against the available drugs. Owing to these challenges, the conventional drug development regimen is further limited by target discovery and ligand suitability for the targets. On the other hand, as an added advantage, the emergence of omics-based tools, such as high-end proteomics, transcriptomics and genomics, has hastened the pace of target discovery and target-based drug development. It is now becoming apparent that multi-omics convergence and an inter-connected systems approach is less time-consuming and more cost-effective for any drug-development process. This comprehensive review is an attempt to summarize the current knowledge on the muti-omics approach in drug development against leishmaniasis. In particular, it elaborates the potential target identification from secreted proteins in various stages of Leishmania infection and also illustrates the convergence of transcriptomic and genomic data towards the collective goal of drug discovery. This review also provides an understanding of the potential parasite's drug targets and drug resistance characteristics of the parasite, which can be used in designing effective and specific therapeutics.

A Cytokine Network Balance Influences the Fate of Leishmania (Viannia) braziliensis Infection in a Cutaneous Leishmaniasis Hamster Model

The golden hamster is a suitable model for studying cutaneous leishmaniasis (CL) due to Leishmania (Viannia) braziliensis. Immunopathological mechanisms are well established in the L. (L.) major-mouse model, in which IL-4 instructs a Th2 response towards progressive infection. In the present study, we evaluated the natural history of L. braziliensis infection from its first stages up to lesion establishment, with the aim of identifying immunological parameters associated with the disease outcome and parasitism fate. To this end, hamsters infected with 10⁴, 10⁵, or 10⁶ promastigotes were monitored during the first hours (4h, 24h), early (15 days, 30 days) and late (50 days) post-infection (pi) phases. Cytokines, iNOS and arginase gene expression were quantified in the established lesions by reverse transcription-quantitative PCR. Compared to the 10⁵ or 10⁶ groups, 10⁴ animals presented lower lesions sizes, less tissue damage, and lower IgG levels. Basal gene expression in normal skin was high for TGF-β, and intermediary for TNF, IL-6, and IL-4. At 4hpi, no cytokine induction was observed in the 10⁴ group, while an upregulation of IL-6, IL-10, and IL-4 was observed in the 10⁶ group. At 15dpi, lesion appearance was accompanied by an increased expression of all assessed cytokines, markedly in the 10⁵ and 10⁶ groups. Upregulation of all investigated cytokines was observed in the late phase, although less expressive in the 10⁴ group. IFN-γ was the depending variable influencing tissue damage, while IL-6 was associated to parasite load. The network correlating gene expression and clinical and laboratorial parameters indicated inoculum-independent associations at 15 and 30dpi. A strong positive network correlation was observed in the 10⁴ group, but not in the 10⁵ or 10⁶ groups. In conclusion, IL-4, IL-6, IL-10, and TGF-β are linked o L. braziliensis progression. However, a balanced cytokine network is the key for an immune response able to reduce the ongoing infection and reduce pathological damage.

Differentially modulated proteins associated with Leishmaniasis-a systematic review of in-vivo and in-vitro studies

High-throughput proteomic technologies are widely used for understanding the disease mechanism, drug-resistant mechanism, and to identify drug targets and markers for diagnostics. Studies with proteomics applications, relating to Leishmaniasis, are being constantly reported in the literature. However, from such studies, a readily accessible knowledge of differentially modulated proteins associated with Leishmaniasis is lacking. Hence, we performed a systematic review concerning differentially modulated proteins (DMP) in Leishmania as well as host infected with Leishmania from the published articles between the years 2000 and 2019. This review is classified into five different sections, namely, DMP in the host after Leishmania infection, DMP between different strains of Leishmania, DMP in drug-resistant Leishmania, DMP in Leishmania under stress, and DMP in different life stages of Leishmania. A lot of consensuses could be observed among the DMP in drug-resistant and stressed Leishmania. In addition to the review, a database was constructed with the data collected in this study (protein accession ID, protein name, gene name, host organism, experimental conditions, fold change, and regulatory data). A total of 2635 records are available in the database. We believe this review and the database will help the researcher in understanding the disease better and provide information for the targeted proteomics study related to Leishmaniasis. Database availability: http://ldepdb.biomedinformri.com/.

Molecular modeling and simulation study of homoserine kinase as an effective leishmanial drug target

Leishmaniasis is a tropical neglected disease that imposes major health concerns in many endemic countries worldwide and requires urgent attention to the identification of new drug targets as well as drug candidates. In the current study, we propose homoserine kinase (HSK) inhibition as a strategy to induce pathogen mortality via generating threonine deficiency. We introduce a homology-based molecular model of leishmanial HSK that appears to possess all conserved structural as well as functional features in the GHMP kinase family. Furthermore, 200 ns molecular dynamics data of the enzyme in open and closed state attempts to provide the mechanistic details involved in the substrate as well as phosphate binding to this enzyme. We discuss the structural and functional significance of movements involved in various loops (motif 1, 2, 3) and lips (upper and lower) in the transition of leishmanial HSK from closed to open state. Virtual screening data of more than 40,000 compounds from the present investigation tries to identify a few potential HSK inhibitors that possess important features to act as efficient HSK inhibitors. These compounds can be considered an effective starting point for the identification of novel drug-like scaffolds. We hope the structural wealth that is offered in this report will be utilized in designing competent experimental and therapeutic interventions for leishmaniasis management. Graphical abstract.

Approaching complexity: systems biology and ms-based techniques to address immune signaling

INTRODUCTION

Studying immune signaling has been critical for our understanding of immunology, pathogenesis, cancer, and homeostasis. To enhance the breadth of the analysis, high throughput methods have been developed to survey multiple areas simultaneously, including transcriptomics, reporter assays, and ELISAs. While these techniques have been extremely informative, mass-spectrometry-based technologies have been gaining momentum and starting to be widely used in the studies of immune signaling and systems immunology.

AREAS COVERED

We present established proteomic methods that have been used to address immune signaling and discuss the new mass-spectrometry- based techniques of interest to the expanding field of systems immunology. Established and new proteomic methods and their applications discussed here include post-translational modification analysis, protein quantification, secretome analysis, and interactomics. In addition, we present developments in small molecule and metabolite analysis, mass spectrometry imaging, and single cell analysis. Finally, we discuss the role of multi-omic integration in aiding leading edge investigation.

EXPERT OPINION

In science, available techniques enhance the breadth and depth of the studies. By incorporating proteomic techniques and their innovative use, it will be possible to expand the current studies and to address novel questions at the forefront of scientific discovery.

Analysis of Spatiotemporal Urine Protein Dynamics to Identify New Biomarkers for Sepsis-Induced Acute Kidney Injury

Acute kidney injury (AKI) is a frequent complication of sepsis and contributes to increased mortality. Discovery of reliable biomarkers could enable identification of individuals with high AKI risk as well as early AKI detection and AKI progression monitoring. However, the current methods are insensitive and non-specific. This study aimed to identify new biomarkers through label-free mass spectrometry (MS) analysis of a sepsis model induced by cecal ligation and puncture (CLP). Urine samples were collected from septic rats at 0, 3, 6, 12, 24, and 48 h. Protein isolated from urine was subjected to MS. Immunoregulatory biological processes, including immunoglobin production and wounding and defense responses, were upregulated at early time points. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses identified 77 significantly changed pathways. We further examined the consistently differentially expressed proteins to seek biomarkers that can be used for early diagnosis. Notably, the expression of PARK7 and CDH16 were changed in a continuous manner and related to the level of Scr in urine from patients. Therefore, PARK7 and CDH16 were confirmed to be novel biomarkers after validation in sepsis human patients. In summary, our study analyzed the proteomics of AKI at multiple time points, elucidated the related biological processes, and identified novel biomarkers for early diagnosis of sepsis-induced AKI, and our findings provide a theoretical basis for further research on the molecular mechanisms.