Proteomics: Concepts and applications in human medicine

Prenatal exposures to endocrine disrupting chemicals: The role of multi-omics in understanding toxicity

Endocrine disrupting chemicals (EDCs) are a diverse group of toxicants detected in populations globally. Prenatal EDC exposures impact birth and childhood outcomes. EDCs work through persistent changes at the molecular, cellular, and organ level. Molecular and biochemical signals or 'omics' can be measured at various functional levels - including the epigenome, transcriptome, proteome, metabolome, and the microbiome. In this narrative review, we introduce each omics and give examples of associations with prenatal EDC exposures. There is substantial research on epigenomic modifications in offspring exposed to EDCs during gestation, and a growing number of studies evaluating the transcriptome, proteome, metabolome, or microbiome in response to these exposures. Multi-omics, integrating data across omics layers, may improve understanding of disrupted function pathways related to early life exposures. We highlight several data integration methods to consider in multi-omics studies. Information from multi-omics can improve understanding of the biological processes and mechanisms underlying prenatal EDC toxicity.

Proteomics provides insights into the theranostic potential of extracellular vesicles

Extracellular vesicles (EVs) encompass a diverse range of membranous structures derived from cells, including exosomes and microvesicles. These vesicles are present in biological fluids and play vital roles in various physiological and pathological processes. They facilitate intercellular communication by enabling the exchange of proteins, lipids, and genetic material between cells. Understanding the cellular processes that govern EV biology is essential for unraveling their physiological and pathological functions and their potential clinical applications. Despite significant advancements in EV research in recent years, there is still much to learn about these vesicles. The advent of improved mass spectrometry (MS)-based techniques has allowed for a deeper characterization of EV protein composition, providing valuable insights into their roles in different physiological and pathological conditions. In this chapter, we provide an overview of proteomics studies conducted to identify the protein contents of EVs, which contribute to their therapeutic and pathological features. We also provided evidence on the potential of EV proteome contents as biomarkers for early disease diagnosis, progression, and treatment response, as well as factors that influence their composition. Additionally, we discuss the available databases containing information on EV proteome contents, and finally, we highlight the need for further research to pave the way toward their utilization in clinical settings.

How is Big Data reshaping preclinical aging research?

The exponential scientific and technological progress during the past 30 years has favored the comprehensive characterization of aging processes with their multivariate nature, leading to the advent of Big Data in preclinical aging research. Spanning from molecular omics to organism-level deep phenotyping, Big Data demands large computational resources for storage and analysis, as well as new analytical tools and conceptual frameworks to gain novel insights leading to discovery. Systems biology has emerged as a paradigm that utilizes Big Data to gain insightful information enabling a better understanding of living organisms, visualized as multilayered networks of interacting molecules, cells, tissues and organs at different spatiotemporal scales. In this framework, where aging, health and disease represent emergent states from an evolving dynamic complex system, context given by, for example, strain, sex and feeding times, becomes paramount for defining the biological trajectory of an organism. Using bioinformatics and artificial intelligence, the systems biology approach is leading to remarkable advances in our understanding of the underlying mechanism of aging biology and assisting in creative experimental study designs in animal models. Future in-depth knowledge acquisition will depend on the ability to fully integrate information from different spatiotemporal scales in organisms, which will probably require the adoption of theories and methods from the field of complex systems. Here we review state-of-the-art approaches in preclinical research, with a focus on rodent models, that are leading to conceptual and/or technical advances in leveraging Big Data to understand basic aging biology and its full translational potential.

Endophytic Bacterium Flexivirga meconopsidis sp. nov. with Plant Growth-Promoting Function, Isolated from the Seeds of Meconopsis integrifolia

Strain Q11T of an irregular coccoid Gram-positive bacterium, aerobic and non-motile, was isolated from Meconopsis integrifolia seeds. Strain Q11T grew optimally in 1% (w/v) NaCl, pH 7, at 30 °C. Strain Q11T is most closely related to Flexivirga, as evidenced by 16S rRNA gene analysis, and shares the highest similarity with Flexivirga aerilata ID2601ST (99.24%). Based on genome sequence analysis, the average nucleotide identity and digital DNA-DNA hybridization values of strains Q11T and D2601ST were 88.82% and 36.20%, respectively. Additionally, strain Q11T showed the abilities of nitrogen fixation and indole acetic acid production and was shown to promote maize growth under laboratory conditions. Its genome contains antibiotic resistance genes (the vanY gene in the vanB cluster and the vanW gene in the vanI cluster) and extreme environment tolerance genes (ectoine biosynthetic gene cluster). Shotgun proteomics also detected antibiotic resistance proteins (class A beta-lactamases, D-alanine ligase family proteins) and proteins that improve plant cold tolerance (multispecies cold shock proteins). Strain Q11T was determined to be a novel species of the genus Flexivirga, for which the name Flexivirga meconopsidis sp. nov. is proposed. The strain type is Q11T (GDMCC 1.3002T = JCM 36020 T).

Advances in neuroproteomics for neurotrauma: unraveling insights for personalized medicine and future prospects

Neuroproteomics, an emerging field at the intersection of neuroscience and proteomics, has garnered significant attention in the context of neurotrauma research. Neuroproteomics involves the quantitative and qualitative analysis of nervous system components, essential for understanding the dynamic events involved in the vast areas of neuroscience, including, but not limited to, neuropsychiatric disorders, neurodegenerative disorders, mental illness, traumatic brain injury, chronic traumatic encephalopathy, and other neurodegenerative diseases. With advancements in mass spectrometry coupled with bioinformatics and systems biology, neuroproteomics has led to the development of innovative techniques such as microproteomics, single-cell proteomics, and imaging mass spectrometry, which have significantly impacted neuronal biomarker research. By analyzing the complex protein interactions and alterations that occur in the injured brain, neuroproteomics provides valuable insights into the pathophysiological mechanisms underlying neurotrauma. This review explores how such insights can be harnessed to advance personalized medicine (PM) approaches, tailoring treatments based on individual patient profiles. Additionally, we highlight the potential future prospects of neuroproteomics, such as identifying novel biomarkers and developing targeted therapies by employing artificial intelligence (AI) and machine learning (ML). By shedding light on neurotrauma's current state and future directions, this review aims to stimulate further research and collaboration in this promising and transformative field.

Metabolomics and mitochondrial dysfunction in cardiometabolic disease

Circulating metabolites are indicators of systemic metabolic dysfunction and can be detected through contemporary techniques in metabolomics. These metabolites are involved in numerous mitochondrial metabolic processes including glycolysis, fatty acid β-oxidation, and amino acid catabolism, and changes in the abundance of these metabolites is implicated in the pathogenesis of cardiometabolic diseases (CMDs). Epigenetic regulation and direct metabolite-protein interactions modulate metabolism, both within cells and in the circulation. Dysfunction of multiple mitochondrial components stemming from mitochondrial DNA mutations are implicated in disease pathogenesis. This review will summarize the current state of knowledge regarding: i) the interactions between metabolites found within the mitochondrial environment during CMDs, ii) various metabolites' effects on cellular and systemic function, iii) how harnessing the power of metabolomic analyses represents the next frontier of precision medicine, and iv) how these concepts integrate to expand the clinical potential for translational cardiometabolic medicine.

Electrosprayed Nanoparticles Containing Mangiferin-Rich Extract from Mango Leaves for Cosmeceutical Application

Mango (Mangifera indica L.) is one of the most economically important fruits in Thailand. Mango has been used as a traditional medicine because it possesses many biological activities, such as antioxidant properties, anti-inflammatory properties, microorganism-growth inhibition, etc. Among its natural pharmacologically active compounds, mangiferin is the main active component found in mango leaves. Mangiferin has the potential to treat a variety of diseases due to its multifunctional activities. This study aims to prepare a mangiferin-rich extract (MRE) from mango leaves and develop nanoparticles containing the MRE using an electrospraying technique to apply it in a cosmeceutical formulation. The potential cosmeceutical mechanisms of the MRE were investigated using proteomic analysis. The MRE is involved in actin-filament organization, the positive regulation of cytoskeleton organization, etc. Moreover, the related mechanism to its cosmeceutical activity is metalloenzyme-activity regulation. Nanoparticles were prepared from 0.8% w/v MRE and 2% w/v Eudragit® L100 solution using an electrospraying process. The mean size of the MRE-loaded nanoparticles (MNPs) received was 247.8 nm, with a PDI 0.271. The MRE entrapment by the process was quantified as 84.9%, indicating a high encapsulation efficiency. For the skin-retention study, the mangiferin content in the MNP-containing emulsion-gel membranes was examined and found to be greater than in the membranes of the MRE solution, illustrating that the MNPs produced by the electrospraying technique help transdermal delivery for cosmetic applications.

Novel putative biomarkers for infective endocarditis by serum proteomic analysis: a comprehensive review of literature

Infective endocarditis (IE) is a challenging condition with high mortality. Prompt detection of IE has become essential for early and immediate management. The authors aimed to comprehensively review the existing literature on novel putative biomarkers for IE through serum proteomic analysis. The literature reveals high levels of N-terminal-pro-B-type natriuretic peptide (NT-proBNP) levels in IE with staphylococcal etiology, valvular lesions, and when combined with cardiac troponin I (cTnI), had a more significant value for risk stratification. A higher pro-ADM level, copeptin, NT-proBNP, and the monocyte-to-high-density lipoprotein cholesterol ratio (MHR) all impacted mortality during the hospital stay. The biomarker matrix metalloproteinase-9 was utilized to predict new-onset embolic events in patients, thus serving as a predictive marker. Procalcitonin was an important diagnostic marker in IE complicated with severe infection. Interleukin-6 (IL-6), Interleukin-8 (IL-8), Interferon-γ, cTnI, and NT-proBNP were also discovered to be useful as prognostic indicators. Early diagnosis and appropriate treatment are possible using antiphospholipid antibodies as a diagnostic test for definite IE. It is also concluded that antineutrophilic cytoplasmic antibody positive individuals with IE had a lengthier hospital stay. These noninvasive biomarkers can identify patients at risk and provide appropriate and early clinical management. NT-proBNP, Cystatin C, troponins, IL-6, IL-8, S100A11, and AQP9 are examples of possible markers that appear promising for further research. In conclusion, large-scale validation studies should study these biomarkers further to establish their use in clinical settings.

Management of Biofilm with Breast Implant Surgery

LEARNING OBJECTIVES

After studying this article, the participant should be able to: 1. Understand how bacteria negatively impact aesthetic and reconstructive breast implants. 2. Understand how bacteria infect breast implants. 3. Understand the evidence associated with common implant infection-prevention strategies, and their limitations. 4. Understand why implementation of bacteria-mitigation strategies such as antibiotic administration or "no-touch" techniques may not indefinitely prevent breast implant infection.

SUMMARY

Bacterial infection of aesthetic and reconstructive breast implants is a common and expensive problem. Subacute infections or chronic capsular contractures leading to device explantation are the most commonly documented sequelae. Although bench and translational research underscores the complexities of implant-associated infection, high-quality studies with adequate power, control groups, and duration of follow-up are lacking. Common strategies to minimize infections use antibiotics-administered systemically, in the breast implant pocket, or by directly bathing the implant before insertion-to limit bacterial contamination. Limiting contact between the implant and skin or breast parenchyma represents an additional common strategy. The clinical prevention of breast implant infection is challenged by the clean-contaminated nature of breast parenchyma, and the variable behavior of not only specific bacterial species but also their strains. These factors impact bacterial virulence and antibiotic resistance.

Closing the Gap in Proteomic Identification of Histoplasma capsulatum: A Case Report and Review of Literature

Histoplasmosis is a globally distributed systemic infection caused by the dimorphic fungus Histoplasma capsulatum (H. capsulatum). This fungus can cause a wide spectrum of clinical manifestations, and the diagnosis of progressive disseminated histoplasmosis is often a challenge for clinicians. Although microscopy and culture remain the gold standard diagnostic tests for Histoplasma identification, matrix-assisted laser desorption ionization time of flight mass spectrometry (MALDI-TOF MS) has emerged as a method of microbial identification suitable for the confirmation of dimorphic fungi. However, to our knowledge, there are no entries for H. capsulatum spectra in most commercial databases. In this review, we describe the case of disseminated histoplasmosis in a patient living with HIV admitted to our university hospital that we failed to identify by the MALDI-TOF method due to the limited reference spectrum of the instrument database. Furthermore, we highlight the utility of molecular approaches, such as conventional polymerase chain reaction (PCR) and DNA sequencing, as alternative confirmatory tests to MALDI-TOF technology for identifying H. capsulatum from positive cultures. An overview of current evidence and limitations of MALDI-TOF-based characterization of H. capsulatum is also presented.

Urinary Peptidomics and Pulse Wave Velocity: The African-PREDICT Study

Increased arterial stiffness is related to early vascular aging and is an independent predictor for cardiovascular disease and mortality. Molecular mechanisms underlying increased arterial stiffness are largely unexplored, especially at the proteome level. We aimed to explore the relationship between pulse wave velocity and urinary proteomics. We included 919 apparently healthy (no chronic illnesses) Black and White men and women (equally distributed) between 20 and 30 years from the African-PREDICT study. Capillary electrophoresis time-of-flight mass spectrometry was used to analyze the urinary proteome. We measured the carotid-femoral pulse wave velocity to estimate arterial stiffness. In the total group, pulse wave velocity correlated positively with collagen-derived peptides including collagen types I, II, III, IV, V, and IX and inversely with collagen type XI (adjusted for mean arterial pressure). Regarding noncollagen-derived peptides, pulse wave velocity positively correlated with polymeric immunoglobulin receptor peptides (n = 2) (all q-value ≤0.05). In multivariable adjusted analyses, pulse wave velocity associated positively and independently with seven urinary peptides (collagen type I, n = 5) (all p-value ≤0.05). We found significant positive and independent associations between pulse wave velocity and the collagen type I-derived peptides, suggesting that dysregulation of collagen type I in the extracellular matrix scaffold could lead to early onset of increased arterial stiffness.

Biomarkers in psychiatric disorders

Psychiatric disorders represent a significant socioeconomic and healthcare burden worldwide. Of these, schizophrenia, bipolar disorder, major depressive disorder and anxiety are among the most prevalent. Unfortunately, diagnosis remains problematic and largely complicated by the lack of disease specific biomarkers. Accordingly, much research has focused on elucidating these conditions to more fully understand underlying pathophysiology and potentially identify biomarkers, especially those of early stage disease. In this chapter, we review current status of this endeavor as well as the potential development of novel biomarkers for clinical applications and future research study.

New Challenges for Anatomists in the Era of Omics

Anatomic studies have traditionally relied on macroscopic, microscopic, and histological techniques to investigate the structure of tissues and organs. Anatomic studies are essential in many fields, including medicine, biology, and veterinary science. Advances in technology, such as imaging techniques and molecular biology, continue to provide new insights into the anatomy of living organisms. Therefore, anatomy remains an active and important area in the scientific field. The consolidation in recent years of some omics technologies such as genomics, transcriptomics, proteomics, and metabolomics allows for a more complete and detailed understanding of the structure and function of cells, tissues, and organs. These have been joined more recently by "omics" such as radiomics, pathomics, and connectomics, supported by computer-assisted technologies such as neural networks, 3D bioprinting, and artificial intelligence. All these new tools, although some are still in the early stages of development, have the potential to strongly contribute to the macroscopic and microscopic characterization in medicine. For anatomists, it is time to hitch a ride and get on board omics technologies to sail to new frontiers and to explore novel scenarios in anatomy.

Blood Proteome Profiling Reveals Biomarkers and Pathway Alterations in Fragile X PM at Risk for Developing FXTAS

Fragile X-associated Tremor/Ataxia Syndrome (FXTAS) is a neurodegenerative disorder associated with the FMR1 premutation. Currently, it is not possible to determine when and if individual premutation carriers will develop FXTAS. Thus, with the aim to identify biomarkers for early diagnosis, development, and progression of FXTAS, along with associated dysregulated pathways, we performed blood proteomic profiling of premutation carriers (PM) who, as part of an ongoing longitudinal study, emerged into two distinct groups: those who developed symptoms of FXTAS (converters, CON) over time (at subsequent visits) and those who did not (non-converters, NCON). We compared these groups to age-matched healthy controls (HC). We assessed CGG repeat allele size by Southern blot and PCR analysis. The proteomic profile was obtained by liquid chromatography mass spectrometry (LC-MS/MS). We identified several significantly differentiated proteins between HC and the PM groups at Visit 1 (V1), Visit 2 (V2), and between the visits. We further reported the dysregulated protein pathways, including sphingolipid and amino acid metabolism. Our findings are in agreement with previous studies showing that pathways involved in mitochondrial bioenergetics, as observed in other neurodegenerative disorders, are significantly altered and appear to contribute to the development of FXTAS. Lastly, we compared the blood proteome of the PM who developed FXTAS over time with the CSF proteome of the FXTAS patients recently reported and found eight significantly differentially expressed proteins in common. To our knowledge, this is the first report of longitudinal proteomic profiling and the identification of unique biomarkers and dysregulated protein pathways in FXTAS.

Perspectives of Proteomics in Respiratory Allergic Diseases

Proteomics in respiratory allergic diseases has such a battery of techniques and programs that one would almost think there is nothing impossible to find, invent or mold. All the resources that we document here are involved in solving problems in allergic diseases, both diagnostic and prognostic treatment, and immunotherapy development. The main perspectives, according to this version, are in three strands and/or a lockout immunological system: (1) Blocking the diapedesis of the cells involved, (2) Modifications and blocking of paratopes and epitopes being understood by modifications to antibodies, antagonisms, or blocking them, and (3) Blocking FcεRI high-affinity receptors to prevent specific IgEs from sticking to mast cells and basophils. These tools and targets in the allergic landscape are, in our view, the prospects in the field. However, there are still many allergens to identify, including some homologies between allergens and cross-reactions, through the identification of structures and epitopes. The current vision of using proteomics for this purpose remains a constant; this is also true for the basis of diagnostic and controlled systems for immunotherapy. Ours is an open proposal to use this vision for treatment.

Precision Medicine: Disease Subtyping and Tailored Treatment

The genomics-based concept of precision medicine began to emerge following the completion of the Human Genome Project. In contrast to evidence-based medicine, precision medicine will allow doctors and scientists to tailor the treatment of different subpopulations of patients who differ in their susceptibility to specific diseases or responsiveness to specific therapies. The current precision medicine model was proposed to precisely classify patients into subgroups sharing a common biological basis of diseases for more effective tailored treatment to achieve improved outcomes. Precision medicine has become a term that symbolizes the new age of medicine. In this review, we examine the history, development, and future perspective of precision medicine. We also discuss the concepts, principles, tools, and applications of precision medicine and related fields. In our view, for precision medicine to work, two essential objectives need to be achieved. First, diseases need to be classified into various subtypes. Second, targeted therapies must be available for each specific disease subtype. Therefore, we focused this review on the progress in meeting these two objectives.

Oncogenic Proteomics Approaches for Translational Research and HIV-Associated Malignancy Mechanisms

Recent advances in the field of proteomics have allowed extensive insights into the molecular regulations of the cell proteome. Specifically, this allows researchers to dissect a multitude of signaling arrays while targeting for the discovery of novel protein signatures. These approaches based on data mining are becoming increasingly powerful for identifying both potential disease mechanisms as well as indicators for disease progression and overall survival predictive and prognostic molecular markers for cancer. Furthermore, mass spectrometry (MS) integrations satisfy the ongoing demand for in-depth biomarker validation. For the purpose of this review, we will highlight the current developments based on MS sensitivity, to place quantitative proteomics into clinical settings and provide a perspective to integrate proteomics data for future applications in cancer precision medicine. We will also discuss malignancies associated with oncogenic viruses such as Acquire Immunodeficiency Syndrome (AIDS) and suggest novel mechanisms behind this phenomenon. Human Immunodeficiency Virus type-1 (HIV-1) proteins are known to be oncogenic per se, to induce oxidative and endoplasmic reticulum stresses, and to be released from the infected or expressing cells. HIV-1 proteins can act alone or in collaboration with other known oncoproteins, which cause the bulk of malignancies in people living with HIV-1 on ART.

Dysregulation of Metabolism and Proteostasis in Skeletal Muscle of a Presymptomatic Pompe Mouse Model

Pompe disease is a rare genetic metabolic disorder caused by mutations in acid-alpha glucoside (GAA) leading to pathological lysosomal glycogen accumulation associated with skeletal muscle weakness, respiratory difficulties and cardiomyopathy, dependent from the GAA residual enzyme activity. This study aimed to investigate early proteomic changes in a mouse model of Pompe disease and identify potential therapeutic pathways using proteomic analysis of skeletal muscles from pre-symptomatic Pompe mice. For this purpose, quadriceps samples of Gaa^6neo/6neo mutant (Pompe) and wildtype mice, at the age of six weeks, were studied with three biological replicates for each group. The data were validated with skeletal muscle morphology, immunofluorescence studies and western blot analysis. Proteomic profiling identified 538 significantly upregulated and 16 significantly downregulated proteins in quadriceps muscles derived from Pompe animals compared to wildtype mice. The majority of significantly upregulated proteins were involved in metabolism, translation, folding, degrading and vesicular transport, with some having crucial roles in the etiopathology of other neurological or neuromuscular diseases. This study highlights the importance of the early diagnosis and treatment of Pompe disease and suggests potential add-on therapeutic strategies targeting protein dysregulations.

A Brief Overview of Neutrophils in Neurological Diseases

Neutrophils are the most abundant leukocyte in circulation and are the first line of defense after an infection or injury. Neutrophils have a broad spectrum of functions, including phagocytosis of microorganisms, the release of pro-inflammatory cytokines and chemokines, oxidative burst, and the formation of neutrophil extracellular traps. Traditionally, neutrophils were thought to be most important for acute inflammatory responses, with a short half-life and a more static response to infections and injury. However, this view has changed in recent years showing neutrophil heterogeneity and dynamics, indicating a much more regulated and flexible response. Here we will discuss the role of neutrophils in aging and neurological disorders; specifically, we focus on recent data indicating the impact of neutrophils in chronic inflammatory processes and their contribution to neurological diseases. Lastly, we aim to conclude that reactive neutrophils directly contribute to increased vascular inflammation and age-related diseases.

Molecular mechanisms augmenting resistance to current therapies in clinics among cervical cancer patients

Cervical cancer (CC) is the fourth leading cause of cancer death (~ 324,000 deaths annually) among women internationally, with 85% of these deaths reported in developing regions, particularly sub-Saharan Africa and Southeast Asia. Human papillomavirus (HPV) is considered the major driver of CC, and with the availability of the prophylactic vaccine, HPV-associated CC is expected to be eliminated soon. However, female patients with advanced-stage cervical cancer demonstrated a high recurrence rate (50-70%) within two years of completing radiochemotherapy. Currently, 90% of failures in chemotherapy are during the invasion and metastasis of cancers related to drug resistance. Although molecular target therapies have shown promising results in the lab, they have had little success in patients due to the tumor heterogeneity fueling resistance to these therapies and bypass the targeted signaling pathway. The last two decades have seen the emergence of immunotherapy, especially immune checkpoint blockade (ICB) therapies, as an effective treatment against metastatic tumors. Unfortunately, only a small subgroup of patients (< 20%) have benefited from this approach, reflecting disease heterogeneity and manifestation with primary or acquired resistance over time. Thus, understanding the mechanisms driving drug resistance in CC could significantly improve the quality of medical care for cancer patients and steer them to accurate, individualized treatment. The rise of artificial intelligence and machine learning has also been a pivotal factor in cancer drug discovery. With the advancement in such technology, cervical cancer screening and diagnosis are expected to become easier. This review will systematically discuss the different tumor-intrinsic and extrinsic mechanisms CC cells to adapt to resist current treatments and scheme novel strategies to overcome cancer drug resistance.

Proteomic Analysis of Hepatic Fibrosis in Human Immunodeficiency Virus-Associated Nonalcoholic Fatty Liver Disease Demonstrates Up-regulation of Immune Response and Tissue Repair Pathways

BACKGROUND

Human immunodeficiency virus (HIV)-associated nonalcoholic fatty liver disease (NAFLD) is characterized by a high prevalence of hepatic fibrosis as a strong clinical predictor of all-cause and liver-specific mortality risk.

METHODS

We leveraged data from an earlier clinical trial to define the circulating proteomic signature of hepatic fibrosis in HIV-associated NAFLD. A total of 183 plasma proteins within 2 high-multiplex panels were quantified at baseline and at 12 months (Olink Cardiovascular III; Immuno-Oncology).

RESULTS

Twenty proteins were up-regulated at baseline among participants with fibrosis stages 2-3 versus 0-1. Proteins most differentially expressed included matrix metalloproteinase 2 (P < .001), insulin-like growth factor-binding protein 7 (P = .001), and collagen α1(I) chain (P = .001). Proteins were enriched within pathways including response to tumor necrosis factor and aminopeptidase activity. Key proteins correlated directly with visceral adiposity and glucose intolerance and inversely with CD4+ T-cell count. Within the placebo-treated arm, 11 proteins differentially increased among individuals with hepatic fibrosis progression over a 12-month period (P < .05).

CONCLUSIONS

Among individuals with HIV-associated NAFLD, hepatic fibrosis was associated with a distinct proteomic signature involving up-regulation of tissue repair and immune response pathways. These findings enhance our understanding of potential mechanisms and biomarkers of hepatic fibrosis in HIV.

Precision diagnostics in children

Medical practice is transforming from a reactive to a pro-active and preventive discipline that is underpinned by precision medicine. The advances in technologies in such fields as genomics, proteomics, metabolomics, transcriptomics and artificial intelligence have resulted in a paradigm shift in our understanding of specific diseases in childhood, greatly enhanced by our ability to combine data from changes within cells to the impact of environmental and population changes. Diseases in children have been reclassified as we understand more about their genomic origin and their evolution. Genomic discoveries, additional 'omics' data and advances such as optical genome mapping have driven rapid improvements in the precision and speed of diagnoses of diseases in children and are now being incorporated into newborn screening, have improved targeted therapies in childhood and have supported the development of predictive biomarkers to assess therapeutic impact and determine prognosis in congenital and acquired diseases of childhood. New medical device technologies are facilitating data capture at a population level to support higher diagnostic accuracy and tailored therapies in children according to predicted population outcome, and digital ecosystems now tailor therapies and provide support for their specific needs. By capturing biological and environmental data as early as possible in childhood, we can understand factors that predict disease or maintain health and track changes across a more extensive longitudinal path. Data from multiple health and external sources over long-time periods starting from birth or even in the in utero environment will provide further clarity about how to sustain health and prevent or predict disease. In this respect, we will not only use data to diagnose disease, but precision diagnostics will aid the 'diagnosis of good health'. The principle of 'start early and change more' will thus underpin the value of applying a personalised medicine approach early in life.

Hepatic proteomic assessment of oral ingestion of titanium dioxide nano fiber (TDNF) in Sprague Dawley rats

Titanium dioxide nanofibers (TDNF) have been widely employed in pigments, sunscreens, paints, ointments, toothpaste and photocatalytic splitting of water. However, their potential toxicity has not been thoroughly examined. The goal of the present study is to examine hepatic effects associated with the ingestion of TDNF. TDNF was fabricated via electrospinning method and characterized. Six to seven weeks old male Sprague Dawley rats ingested (oral gavage) a total of 0 ppm, 40, 60 ppm TDNF for two weeks. After sacrifice, the liver was assessed for cellular effects using proteomic approach. The fibers diameter ranged from 0.18 - 0.29 μm, forming clusters and majority of the fibers were in the rutile phase. Proteomics assessment revealed more that more than 400 hundred proteins in the liver may be affected. These proteins are involved in such processes as catalysis of fatty acids by CoA, homocysteine metabolism, beta oxidation and the condensation of carbamoyl phosphate in the urea cycle among others. Further analysis of the protein associations showed that 325 biological processes, 140 molecular functions and 70 cellular components appear to be affected from the ingestion of TNDF. Quantitative analysis of specific mRNA transcripts indicated CMBL, GSTM1 and SDS were differentially expressed.

Proteomics in Inherited Metabolic Disorders

Inherited metabolic disorders (IMD) are rare medical conditions caused by genetic defects that interfere with the body's metabolism. The clinical phenotype is highly variable and can present at any age, although it more often manifests in childhood. The number of treatable IMDs has increased in recent years, making early diagnosis and a better understanding of the natural history of the disease more important than ever. In this review, we discuss the main challenges faced in applying proteomics to the study of IMDs, and the key advances achieved in this field using tandem mass spectrometry (MS/MS). This technology enables the analysis of large numbers of proteins in different body fluids (serum, plasma, urine, saliva, tears) with a single analysis of each sample, and can even be applied to dried samples. MS/MS has thus emerged as the tool of choice for proteome characterization and has provided new insights into many diseases and biological systems. In the last 10 years, sequential window acquisition of all theoretical fragmentation spectra mass spectrometry (SWATH-MS) has emerged as an accurate, high-resolution technique for the identification and quantification of proteins differentially expressed between healthy controls and IMD patients. Proteomics is a particularly promising approach to help obtain more information on rare genetic diseases, including identification of biomarkers to aid early diagnosis and better understanding of the underlying pathophysiology to guide the development of new therapies. Here, we summarize new and emerging proteomic technologies and discuss current uses and limitations of this approach to identify and quantify proteins. Moreover, we describe the use of proteomics to identify the mechanisms regulating complex IMD phenotypes; an area of research essential to better understand these rare disorders and many other human diseases.

Discovery of Schistosoma mekongi circulating proteins and antigens in infected mouse sera

Schistosomiasis is a neglected tropical disease caused by an infection of the parasitic flatworms schistosomes. Schistosoma mekongi is a restricted Schistosoma species found near the Mekong River, mainly in southern Laos and northern Cambodia. Because there is no vaccine or effective early diagnosis available for S. mekongi, additional biomarkers are required. In this study, serum biomarkers associated with S. mekongi-infected mice were identified at 14-, 28-, 42-, and 56-days post-infection. Circulating proteins and antigens of S. mekongi in mouse sera were analyzed using mass spectrometry-based proteomics. Serine protease inhibitors and macrophage erythroblast attacher were down-regulated in mouse sera at all infection timepoints. In addition, 54 circulating proteins and 55 antigens of S. mekongi were identified. Notable circulating proteins included kyphoscoliosis peptidase and putative tuberin, and antigens were detected at all four infection timepoints, particularly in the early stages (12 days). The putative tuberin sequence of S. mekongi was highly similar to homologs found in other members of the genus Schistosoma and less similar to human and murine sequences. Our study provided the identity of promising diagnostic biomarkers that could be applicable in early schistosomiasis diagnosis and vaccine development.

Exploring COVID-19 pathogenesis on command-line: A bioinformatics pipeline for handling and integrating omics data

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was first identified in late 2019 in Wuhan, China, and has proven to be highly pathogenic, making it a global public health threat. The immediate need to understand the mechanisms and impact of the virus made omics techniques stand out, as they can offer a holistic and comprehensive view of thousands of molecules in a single experiment. Mastering bioinformatics tools to process, analyze, integrate, and interpret omics data is a powerful knowledge to enrich results. We present a robust and open access computational pipeline for extracting information from quantitative proteomics and transcriptomics public data. We present the entire pipeline from raw data to differentially expressed genes. We explore processes and pathways related to mapped transcripts and proteins. A pipeline is presented to integrate and compare proteomics and transcriptomics data using also packages available in the Bioconductor and providing the codes used. Cholesterol metabolism, immune system activity, ECM, and proteasomal degradation pathways increased in infected patients. Leukocyte activation profile was overrepresented in both proteomics and transcriptomics data. Finally, we found a panel of proteins and transcripts regulated in the same direction in the lung transcriptome and plasma proteome that distinguish healthy and infected individuals. This panel of markers was confirmed in another cohort of patients, thus validating the robustness and functionality of the tools presented.

A multi-omics study of the anti-cancer effect of a ferulic acid derivative FA-30

The active ingredients of Traditional Chinese Medicine are an important source of bioactive molecules and play an important role in the research and development of innovative drugs.