Omics study reveals abnormal alterations of breastmilk proteins and metabolites in puerperant women with COVID-19

Molecular epidemiology of pregnancy using omics data: advances, success stories, and challenges

Multi-omics approaches have been successfully applied to investigate pregnancy and health outcomes at a molecular and genetic level in several studies. As omics technologies advance, research areas are open to study further. Here we discuss overall trends and examples of successfully using omics technologies and techniques (e.g., genomics, proteomics, metabolomics, and metagenomics) to investigate the molecular epidemiology of pregnancy. In addition, we outline omics applications and study characteristics of pregnancy for understanding fundamental biology, causal health, and physiological relationships, risk and prediction modeling, diagnostics, and correlations.

COVIDpro: Database for Mining Protein Dysregulation in Patients with COVID-19

The ongoing pandemic of the coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 still has limited treatment options. Our understanding of the molecular dysregulations that occur in response to infection remains incomplete. We developed a web application COVIDpro (https://www.guomics.com/covidPro/) that includes proteomics data obtained from 41 original studies conducted in 32 hospitals worldwide, involving 3077 patients and covering 19 types of clinical specimens, predominantly plasma and serum. The data set encompasses 53 protein expression matrices, comprising a total of 5434 samples and 14,403 unique proteins. We identified a panel of proteins that exhibit significant dysregulation, enabling the classification of COVID-19 patients into severe and non-severe disease categories. The proteomic signatures achieved promising results in distinguishing severe cases, with a mean area under the curve of 0.87 and accuracy of 0.80 across five independent test sets. COVIDpro serves as a valuable resource for testing hypotheses and exploring potential targets for novel treatments in COVID-19 patients.

Untargeted Metabolomic Analysis of Lactation-Stage-Matched Human and Bovine Milk Samples at 2 Weeks Postnatal

Epidemiological data demonstrate that bovine whole milk is often substituted for human milk during the first 12 months of life and may be associated with adverse infant outcomes. The objective of this study is to interrogate the human and bovine milk metabolome at 2 weeks of life to identify unique metabolites that may impact infant health outcomes. Human milk (n = 10) was collected at 2 weeks postpartum from normal-weight mothers (pre-pregnant BMI < 25 kg/m2) that vaginally delivered term infants and were exclusively breastfeeding their infant for at least 2 months. Similarly, bovine milk (n = 10) was collected 2 weeks postpartum from normal-weight primiparous Holstein dairy cows. Untargeted data were acquired on all milk samples using high-resolution liquid chromatography-high-resolution tandem mass spectrometry (HR LC-MS/MS). MS data pre-processing from feature calling to metabolite annotation was performed using MS-DIAL and MS-FLO. Our results revealed that more than 80% of the milk metabolome is shared between human and bovine milk samples during early lactation. Unbiased analysis of identified metabolites revealed that nearly 80% of milk metabolites may contribute to microbial metabolism and microbe-host interactions. Collectively, these results highlight untargeted metabolomics as a potential strategy to identify unique and shared metabolites in bovine and human milk that may relate to and impact infant health outcomes.

Colostrum Features of Active and Recovered COVID-19 Patients Revealed Using Next-Generation Proteomics Technique, SWATH-MS

Colostrum performs nutritional, anti-inflammatory and anti-infective functions and promotes immune system formation and organ development. The new coronavirus, SARS-CoV-2, has generated concerns about viral transmission through human milk, with a lack of evidence about human milk's protective effects against the infection. This study aimed at analyzing presence of the virus and at identifying the protein expression profile of human colostrum in active and COVID-19-recovered patients. Colostrum samples were collected from women with COVID-19 (n = 3), women recently recovered from the infection (n = 4), and non-infected women (n = 5). The samples were analyzed by means of RT-qPCR to determine presence of the virus and using SWATH-MS for proteomic analysis. Proteomic results were then analyzed using bioinformatic methods. The viral tests were negative for SARS-CoV-2 in the colostrum from COVID-19 patients. The proteomic analysis identified 301 common proteins in all samples analyzed. Nineteen proteins were upregulated and 7 were downregulated in the COVID-19 group versus the control samples, whereas 18 were upregulated and 7 were downregulated when comparing the COVID-19 group to the recovered group. Eleven proteins were biomarkers of active COVID-19 infection. Ten were upregulated: ACTN1, CD36, FAM3B, GPRC5B, IGHA2, IGK, PLTP, RAC1, SDCBP and SERPINF1, and one was downregulated: PSAP. These proteins are mainly related to immunity, inflammatory response and protein transport. In conclusion, the results of this study suggest that colostrum is not a vehicle for mother-to-child SARS-CoV-2 transmission. Moreover, the colostrum's proteome of active and recuperated patients indicate that it could provide immune benefits to infants.

The Impact of the Human Milk Microbiota in the Prevention of Disease and Infant Health

Background: Human milk is recognized as an ideal food for newborns and infants owing to the presence of various nutritive factors, including healthy bacteria. Aim/Objective: This review aimed to understand the effects of human milk microbiota in both the prevention of disease and the health of infants. Methods: Data were obtained from PubMed, Scopus, Web of Science, clinical trial registries, Dergipark, and Türk Atıf Dizini up to February 2023 without language restrictions. Results: It is considered that the first human milk microbiota ingested by the newborn creates the initial microbiome of the gut system, which in turn influences the development and maturation of immunity. Bacteria present in human milk modulate the anti-inflammatory response by releasing certain cytokines, protecting the newborn against certain infections. Therefore, certain bacterial strains isolated from human milk could serve as potential probiotics for various therapeutic applications. Conclusions: In this review, the origin and significance of human milk bacteria have been highlighted along with certain factors influencing the composition of human milk microbiota. In addition, it also summarizes the health benefits of human milk as a protective agent against certain diseases and ailments.

Metabolomics as a powerful tool for diagnostic, pronostic and drug intervention analysis in COVID-19

COVID-19 currently represents one of the major health challenges worldwide. Albeit its infectious character, with onset affectation mainly at the respiratory track, it is clear that the pathophysiology of COVID-19 has a systemic character, ultimately affecting many organs. This feature enables the possibility of investigating SARS-CoV-2 infection using multi-omic techniques, including metabolomic studies by chromatography coupled to mass spectrometry or by nuclear magnetic resonance (NMR) spectroscopy. Here we review the extensive literature on metabolomics in COVID-19, that unraveled many aspects of the disease including: a characteristic metabotipic signature associated to COVID-19, discrimination of patients according to severity, effect of drugs and vaccination treatments and the characterization of the natural history of the metabolic evolution associated to the disease, from the infection onset to full recovery or long-term and long sequelae of COVID.

RaMP-DB 2.0: a renovated knowledgebase for deriving biological and chemical insight from metabolites, proteins, and genes

MOTIVATION

Functional interpretation of high-throughput metabolomic and transcriptomic results is a crucial step in generating insight from experimental data. However, pathway and functional information for genes and metabolites are distributed among many siloed resources, limiting the scope of analyses that rely on a single knowledge source.

RESULTS

RaMP-DB 2.0 is a web interface, relational database, API and R package designed for straightforward and comprehensive functional interpretation of metabolomic and multi-omic data. RaMP-DB 2.0 has been upgraded with an expanded breadth and depth of functional and chemical annotations (ClassyFire, LIPID MAPS, SMILES, InChIs, etc.), with new data types related to metabolites and lipids incorporated. To streamline entity resolution across multiple source databases, we have implemented a new semi-automated process, thereby lessening the burden of harmonization and supporting more frequent updates. The associated RaMP-DB 2.0 R package now supports queries on pathways, common reactions (e.g. metabolite-enzyme relationship), chemical functional ontologies, chemical classes and chemical structures, as well as enrichment analyses on pathways (multi-omic) and chemical classes. Lastly, the RaMP-DB web interface has been completely redesigned using the Angular framework.

AVAILABILITY AND IMPLEMENTATION

The code used to build all components of RaMP-DB 2.0 are freely available on GitHub at https://github.com/ncats/ramp-db, https://github.com/ncats/RaMP-Client/ and https://github.com/ncats/RaMP-Backend. The RaMP-DB web application can be accessed at https://rampdb.nih.gov/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Microbiota-host crosstalk in the newborn and adult rumen at single-cell resolution

BACKGROUND

The rumen is the hallmark organ of ruminants, playing a vital role in their nutrition and providing products for humans. In newborn suckling ruminants milk bypasses the rumen, while in adults this first chamber of the forestomach has developed to become the principal site of microbial fermentation of plant fibers. With the advent of single-cell transcriptomics, it is now possible to study the underlying cell composition of rumen tissues and investigate how this relates the development of mutualistic symbiosis between the rumen and its epithelium-attached microbes.

RESULTS

We constructed a comprehensive cell landscape of the rumen epithelium, based on single-cell RNA sequencing of 49,689 high-quality single cells from newborn and adult rumen tissues. Our single-cell analysis identified six immune cell subtypes and seventeen non-immune cell subtypes of the rumen. On performing cross-species analysis of orthologous genes expressed in epithelial cells of cattle rumen and the human stomach and skin, we observed that the species difference overrides any cross-species cell-type similarity. Comparing adult with newborn cattle samples, we found fewer epithelial cell subtypes and more abundant immune cells, dominated by T helper type 17 cells in the rumen tissue of adult cattle. In newborns, there were more fibroblasts and myofibroblasts, an IGFBP3⁺ epithelial cell subtype not seen in adults, while dendritic cells were the most prevalent immune cell subtype. Metabolism-related functions and the oxidation-reduction process were significantly upregulated in adult rumen epithelial cells. Using 16S rDNA sequencing, fluorescence in situ hybridization, and absolute quantitative real-time PCR, we found that epithelial Desulfovibrio was significantly enriched in the adult cattle. Integrating the microbiome and metabolome analysis of rumen tissues revealed a high co-occurrence probability of Desulfovibrio with pyridoxal in the adult cattle compared with newborn ones while the scRNA-seq data indicated a stronger ability of pyroxidal binding in the adult rumen epithelial cell subtypes. These findings indicate that Desulfovibrio and pyridoxal likely play important roles in maintaining redox balance in the adult rumen.

CONCLUSIONS

Our integrated multi-omics analysis provides novel insights into rumen development and function and may facilitate the future precision improvement of rumen function and milk/meat production in cattle.

COVIDpro: Database for mining protein dysregulation in patients with COVID-19

Background

The ongoing pandemic of the coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) still has limited treatment options partially due to our incomplete understanding of the molecular dysregulations of the COVID-19 patients. We aimed to generate a repository and data analysis tools to examine the modulated proteins underlying COVID-19 patients for the discovery of potential therapeutic targets and diagnostic biomarkers.

Methods

We built a web server containing proteomic expression data from COVID-19 patients with a toolset for user-friendly data analysis and visualization. The web resource covers expert-curated proteomic data from COVID-19 patients published before May 2022. The data were collected from ProteomeXchange and from select publications via PubMed searches and aggregated into a comprehensive dataset. Protein expression by disease subgroups across projects was compared by examining differentially expressed proteins. We also visualize differentially expressed pathways and proteins. Moreover, circulating proteins that differentiated severe cases were nominated as predictive biomarkers.

Findings

We built and maintain a web server COVIDpro ( https://www.guomics.com/covidPro/ ) containing proteomics data generated by 41 original studies from 32 hospitals worldwide, with data from 3077 patients covering 19 types of clinical specimens, the majority from plasma and sera. 53 protein expression matrices were collected, for a total of 5434 samples and 14,403 unique proteins. Our analyses showed that the lipopolysaccharide-binding protein, as identified in the majority of the studies, was highly expressed in the blood samples of patients with severe disease. A panel of significantly dysregulated proteins was identified to separate patients with severe disease from non-severe disease. Classification of severe disease based on these proteomic signatures on five test sets reached a mean AUC of 0.87 and ACC of 0.80.

Interpretation

COVIDpro is an online database with an integrated analysis toolkit. It is a unique and valuable resource for testing hypotheses and identifying proteins or pathways that could be targeted by new treatments of COVID-19 patients.

Funding

National Key R&D Program of China: Key PDPM technologies (2021YFA1301602, 2021YFA1301601, 2021YFA1301603), Zhejiang Provincial Natural Science Foundation for Distinguished Young Scholars (LR19C050001), Hangzhou Agriculture and Society Advancement Program (20190101A04), National Natural Science Foundation of China (81972492) and National Science Fund for Young Scholars (21904107), National Resource for Network Biology (NRNB) from the National Institute of General Medical Sciences (NIGMS-P41 GM103504).

Research in context

Evidence before this study: Although an increasing number of therapies against COVID-19 are being developed, they are still insufficient, especially with the rise of new variants of concern. This is partially due to our incomplete understanding of the disease’s mechanisms. As data have been collected worldwide, several questions are now worth addressing via meta-analyses. Most COVID-19 drugs function by targeting or affecting proteins. Effectiveness and resistance to therapeutics can be effectively assessed via protein measurements. Empowered by mass spectrometry-based proteomics, protein expression has been characterized in a variety of patient specimens, including body fluids (e.g., serum, plasma, urea) and tissue (i.e., formalin-fixed and paraffin-embedded (FFPE)). We expert-curated proteomic expression data from COVID-19 patients published before May 2022, from the largest proteomic data repository ProteomeXhange as well as from literature search engines. Using this resource, a COVID-19 proteome meta-analysis could provide useful insights into the mechanisms of the disease and identify new potential drug targets.Added value of this study: We integrated many published datasets from patients with COVID-19 from 11 nations, with over 3000 patients and more than 5434 proteome measurements. We collected these datasets in an online database, and generated a toolbox to easily explore, analyze, and visualize the data. Next, we used the database and its associated toolbox to identify new proteins of diagnostic and therapeutic value for COVID-19 treatment. In particular, we identified a set of significantly dysregulated proteins for distinguishing severe from non-severe patients using serum samples.Implications of all the available evidence: COVIDpro will support the navigation and analysis of patterns of dysregulated proteins in various COVID-19 clinical specimens for identification and verification of protein biomarkers and potential therapeutic targets.

Spectroscopic methods for COVID-19 detection and early diagnosis

The coronavirus pandemic is a worldwide hazard that poses a threat to millions of individuals throughout the world. This pandemic is caused by the severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2), which was initially identified in Wuhan, China's Hubei provincial capital, and has since spread throughout the world. According to the World Health Organization's Weekly Epidemiological Update, there were more than 250 million documented cases of coronavirus infections globally, with five million fatalities. Early detection of coronavirus does not only reduce the spread of the virus, but it also increases the chance of curing the infection. Spectroscopic techniques have been widely used in the early detection and diagnosis of COVID-19 using Raman, Infrared, mass spectrometry and fluorescence spectroscopy. In this review, the reported spectroscopic methods for COVID-19 detection were discussed with emphasis on the practical aspects, limitations and applications.

Breastfeeding during the COVID-19 pandemic: what do we know so far?

Objective

This study aimed to conduct a literature review on safety in breastfeeding in mothers with COVID-19. An integrative review of national and international literature was carried out.

Methods

The search took place in the SciELO, LILACS and MEDLINE^® databases.

Results

A total of 25 scientific articles that specifically addressed the theme of breastfeeding and its risk and protective factors for infection by SARS-CoV-2 were selected. According to the studies analyzed, although the presence of viral RNA had already been detected by reverse transcriptase polymerase chain reaction in breast milk samples, there are still no proven cases of vertical transmission via human milk.

Conclusion

Breastfeeding appears to be safe if practiced according to precaution measures recommended by the World Health Organization. In addition, there is evidence of a potential for immunological protection by transfer of antibodies against SARS-CoV-2 in breast milk. Breastfeeding should continue to be promoted even in cases of mothers with clinical suspicion or confirmation of COVID-19, as well as the provision of expressed breast milk in cases where there is no possibility of direct breastfeeding.

Metallomic and Untargeted Metabolomic Signatures of Human Milk from SARS-CoV-2 Positive Mothers

Scope

Lack of information about the impact of maternal severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) infection on the elemental and metabolomic profile of human milk (HM).

Methods and results

An observational study on HM from mothers with COVID‐19 is conducted including a prepandemic control group. Maternal–infant clinical records and symptomatology are recorded. The absolute quantification of elements and untargeted relative metabolomic profiles are determined by inductively coupled plasma mass spectrometry and gas chromatography coupled to mass spectrometry, respectively. Associations of HM SARS‐CoV‐2 antibodies with elemental and metabolomic profiles are studied. COVID‐19 has a significant impact on HM composition. COVID‐19 reduces the concentrations of Fe, Cu, Se, Ni, V, and Aluminium (Al) and increases Zn compared to prepandemic control samples. A total of 18 individual metabolites including amino acids, peptides, fatty acids and conjugates, purines and derivatives, alcohols, and polyols are significantly different in HM from SARS‐CoV‐2 positive mothers. Aminoacyl‐tRNA biosynthesis, phenylalanine, tyrosine and tryptophan biosynthesis, phenylalanine, and linoleic acid pathways are significantly altered. Differences are obtained depending on COVID‐19 symptomatic and asymptomatic status.

Conclusions

This study provides unique insights about the impact of maternal SARS‐CoV‐2 infection on the elemental and metabolomic profiles of HM that warrants further research due the potential implications for infant health.

Detectable SARS-CoV-2 in Human Breast Milk: A Turkey Experience

Breastfeeding is considered the strongest postnatal bond between mother and baby and is the best source of nutrition that has implications for infant health and development. However, the global COVID-19 epidemic process and the lack of full understanding of vertical transmission of SARS-CoV-2 have significantly reduced breastfeeding practice. The aim of this study is to investigate the presence of SARS-CoV-2 virus in the milk of lactating mothers with COVID-19 disease and to provide scientific evidence on whether breastfeeding will be safe. For this purpose, breast milk samples were collected from 60 women with COVID-19 in Şanlıurfa city of Turkey, and breast milk samples were tested for the presence of SARS-CoV-2 RNA by RT-PCRs. As a result of the analysis, SARS-CoV-2 RNA was not detected in any breast milk. According to the results obtained in this study, it was concluded that there is no evidence of mother-to-child transmission of SARS-CoV-2 through breast milk and that mothers can safely breastfeed their children in this process. We think that it will be possible with more in-depth analyzes and comprehensive studies to fully understand whether the SARS-CoV-2 virus is transmitted to infants through breast milk.

Sera Metabolomics Characterization of Patients at Different Stages in Wuhan Identifies Critical Biomarkers of COVID-19

We have witnessed the 2-year-long global rampage of COVID-19 caused by the wide spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, knowledge about biomarkers of the entire COVID-19 process is limited. Identification of the systemic features of COVID-19 will lead to critical biomarkers and therapeutic targets for early intervention and clinical disease course prediction. Here, we performed a comprehensive analysis of clinical measurements and serum metabolomics in 199 patients with different stages of COVID-19. In particular, our study is the first serum metabolomic analysis of critical rehabilitation patients and critical death patients. We found many differential metabolites in the comparison of metabolomic results between ordinary, severe, and critical patients and uninfected patients. Through the metabolomic results of COVID-19 patients in various stages, and critical rehabilitation patients and critical death patients, we identified a series of differential metabolites as biomarkers, a separate queue and precise distinction, and predicted COVID-19 verification. These differentially expressed metabolites, included 1,2-di-(9Z,12Z-octadecadienoyl)-sn-glycero-3-phosphate, propylparaben, 20-hydroxyeicosatetraenoic acid, triethanolamine, chavicol, disialosyl galactosyl globoside, 1-arachidonoylglycerophosphoinositol, and alpha-methylstyrene, all of which have been identified for the first time as biomarkers in COVID-19 progression. These biomarkers are involved in many pathological and physiological pathways of COVID-19, for example, immune responses, platelet degranulation, and metabolism which might result in pathogenesis. Our results showed valuable information about metabolites obviously altered in COVID-19 patients with different stages, which could shed light on the pathogenesis as well as serve as potential therapeutic agents of COVID-19.

Composition of Human Breast Milk Microbiota and Its Role in Children's Health

Human milk contains a number of nutritional and bioactive molecules including microorganisms that constitute the so-called "Human Milk Microbiota (HMM)". Recent studies have shown that not only bacterial but also viral, fungal, and archaeal components are present in the HMM. Previous research has established, a "core" microbiome, consisting of Firmicutes (i.e., Streptococcus, Staphylococcus), Proteobacteria (i.e., Serratia, Pseudomonas, Ralstonia, Sphingomonas, Bradyrhizobium), and Actinobacteria (i.e., Propionibacterium, Corynebacterium). This review aims to summarize the main characteristics of HMM and the role it plays in shaping a child's health. We reviewed the most recent literature on the topic (2019-2021), using the PubMed database. The main sources of HMM origin were identified as the retrograde flow and the entero-mammary pathway. Several factors can influence its composition, such as maternal body mass index and diet, use of antibiotics, time and type of delivery, and mode of breastfeeding. The COVID-19 pandemic, by altering the mother-infant dyad and modifying many of our previous habits, has emerged as a new risk factor for the modification of HMM. HMM is an important contributor to gastrointestinal colonization in children and therefore, it is fundamental to avoid any form of perturbation in the HMM that can alter the microbial equilibrium, especially in the first 100 days of life. Microbial dysbiosis can be a trigger point for the development of necrotizing enterocolitis, especially in preterm infants, and for onset of chronic diseases, such as asthma and obesity, later in life.

Potential effects of COVID-19 on reproductive health: a mini review

Coronavirus disease 2019 (COVID-19) is now a major public health problem worldwide. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infectivity is extremely strong. One major target of the virus is the lung, which can lead to death due to the development of respiratory distress syndrome and even multiple system organ failure. The possible pathophysiology by which SARS-CoV-2 affects the object is by way of the receptor, angiotensin-converting enzyme 2 (ACE2). From the study of the viral structure and infection mechanisms, researchers have discovered that the ACE2 acts as a receptor for SARS-CoV-2. According to previous studies, ACE2 is one of the key enzymes in the RAS system. Physiological functions can be found in angiosarcomas and in the kidney, liver, intestine and so on. Whether SARS-CoV-2 infection leads to male fertility impairment has recently received attention. Nevertheless, the association between SARS-CoV-2 infection and reproductive health is currently poorly understood. Using key words including "SARS-CoV-2", "reproductive health", "ACE2" and "2019-nCoV", we retrieved original articles and reviews from the PubMed and WEB OF SCI databases published before December 16, 2020 and performed a thorough review of them. Compared with females, we discovered that infected person with SARS-CoV-2 was higher in males. Men who were infected with SARS-CoV-2 may be easy to suffer from impaired reproductive health. These investigations would help for a comprehensive grasp of the relationship between SARS-CoV-2 infection and reproductive health.

Multiomics integration-based molecular characterizations of COVID-19

The coronavirus disease 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), rapidly became a global health challenge, leading to unprecedented social and economic consequences. The mechanisms behind the pathogenesis of SARS-CoV-2 are both unique and complex. Omics-scale studies are emerging rapidly and offer a tremendous potential to unravel the puzzle of SARS-CoV-2 pathobiology, as well as moving forward with diagnostics, potential drug targets, risk stratification, therapeutic responses, vaccine development and therapeutic innovation. This review summarizes various aspects of understanding multiomics integration-based molecular characterizations of COVID-19, which to date include the integration of transcriptomics, proteomics, genomics, lipidomics, immunomics and metabolomics to explore virus targets and developing suitable therapeutic solutions through systems biology tools. Furthermore, this review also covers an abridgment of omics investigations related to disease pathogenesis and virulence, the role of host genetic variation and a broad array of immune and inflammatory phenotypes contributing to understanding COVID-19 traits. Insights into this review, which combines existing strategies and multiomics integration profiling, may help further advance our knowledge of COVID-19.

Plasma Lipidomic and Metabolomic Profiling after Birth in Neonates Born to SARS-CoV-19 Infected and Non-Infected Mothers at Delivery: Preliminary Results

Pregnant women are among the high-risk populations for COVID-19, whereas the risk of vertical transmission to the fetus is very low. Nevertheless, metabolic alternations described in COVID-19 patients may also occur in pregnant women and their offspring. We prospectively evaluated the plasma lipidomic and metabolomic profiles, soon after birth, in neonates born to infected mothers (cases, n = 10) and in the offspring of uninfected ones at delivery (controls, n = 10). All cases had two negative tests for SARS-CoV-2 (nasopharyngeal swabs) performed 72 h apart. Blood samples were obtained within the first hours after birth. Liquid chromatography-high resolution mass spectrometry (UHPLC-TOF/MS) and gas chromatography-mass spectrometry (GC-MS) were applied for the analyses. Multivariate statistical analysis was performed for data evaluation. Changes in several plasma lipid species-classes (long-chain fatty acids phosphatidylcholines, triglycerides), and amino-acids were identified that allowed for clear discrimination between the study groups. The results of this preliminary investigation suggest that neonates born to Sars-Cov-19 positive mothers, without evidence of viral infection at birth, have a distinct plasma lipidomic and metabolomic profile compared to those of uninfected mothers. Whether these findings are reflective of maternal metabolic alternations due to the virus or a metabolic response following an unidentified neonatal infection warrants further investigation.

An integrative proteomics metabolomics based strategy reveals the mechanisms involved in wasp sting induced acute kidney injury

The pathophysiological mechanisms involved in wasp-sting-induced acute kidney injury (AKI) remain largely unknown. Here, we combined proteomics and metabolomics to investigate the mechanisms behind multiple wasp sting-induced AKI. Interestingly, we found many differentially abundant proteins in the serum of AKI group compared with that of the non-AKI and control groups, involved in several metabolic pathways and the regulation of cellular processes. In addition, we also detected differentially abundant metabolites in the AKI group; among them many were involved in the glycerophospholipid metabolic pathway (the key pathway in the context of AKI): 50 metabolites, all downregulated in the AKI group. Importantly, the convergent analysis of metabolomics and proteomics data revealed that biomarkers of rhabdomyolysis (CA 3, MYL3, and LDH) and hemolysis (ALT and LDH) were integrated into a regulatory network with phospholipid metabolism products in the AKI group, indicating that wasp sting-induced AKI is secondary to rhabdomyolysis and intravascular hemolysis. Of note, such a phenotype suggests the disruption of the membrane of skeletal muscle cells and red blood cells mediated by the phospholipase A1 (PLA1), PLA2, and mastoparan in the wasp venom, via the disruption of membrane glycerophospholipids. Overall, our results highlight a potential new mechanism behind wasp sting-induced AKI and suggest that PLA inhibitors may be potential agents for the treatment of this condition.

Recent omics-based computational methods for COVID-19 drug discovery and repurposing

The coronavirus disease 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is the main reason for the increasing number of deaths worldwide. Although strict quarantine measures were followed in many countries, the disease situation is still intractable. Thus, it is needed to utilize all possible means to confront this pandemic. Therefore, researchers are in a race against the time to produce potential treatments to cure or reduce the increasing infections of COVID-19. Computational methods are widely proving rapid successes in biological related problems, including diagnosis and treatment of diseases. Many efforts in recent months utilized Artificial Intelligence (AI) techniques in the context of fighting the spread of COVID-19. Providing periodic reviews and discussions of recent efforts saves the time of researchers and helps to link their endeavors for a faster and efficient confrontation of the pandemic. In this review, we discuss the recent promising studies that used Omics-based data and utilized AI algorithms and other computational tools to achieve this goal. We review the established datasets and the developed methods that were basically directed to new or repurposed drugs, vaccinations and diagnosis. The tools and methods varied depending on the level of details in the available information such as structures, sequences or metabolic data.

Human bronchial-pulmonary proteomics in coronavirus disease 2019 (COVID-19) pandemic: applications and implications

INTRODUCTION

The outbreak of the newly discovered human coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has disrupted the normal life of almost every civilization worldwide. Studies have shown that the coronavirus disease 2019 (COVID-19) caused by the SARS-CoV-2 can affect multiple human organs and physiological systems, but the respiratory system remains the primary location for viral infection.

AREAS COVERED

We summarize how omics technologies are used in SARS-CoV-2 research and specifically review the current knowledge of COVID-19 from the aspect of human bronchial-pulmonary proteomics. Also, knowledge gaps in COVID-19 that can be fulfilled by proteomics are discussed.

EXPERT OPINION

Overall, human bronchial-pulmonary proteomics plays an important role in revealing the dynamics, functions, tropism, and pathogenicity of SARS-CoV-2, which is crucial for COVID-19 biomarker and therapeutic target discoveries. To more fully understand the impact of COVID-19, research from various angles using multi-omics approaches should also be conducted on the lungs as well as other organs.

Mass Spectrometry-Based Human Breath Analysis: Towards COVID-19 Diagnosis and Research

COVID-19 is a highly contagious respiratory disease that can be infected through human exhaled breath. Human breath analysis is an attractive strategy for rapid diagnosis of COVID-19 in a non-invasive way by monitoring breath biomarkers. Mass spectrometry (MS)-based approaches offer a promising analytical platform for human breath analysis due to their high speed, specificity, sensitivity, reproducibility, and broad coverage, as well as its versatile coupling methods with different chromatographic separation, and thus can lead to a better understanding of the clinical and biochemical processes of COVID-19. Herein, we try to review the developments and applications of MS-based approaches for multidimensional analysis of COVID-19 breath samples, including metabolites, proteins, microorganisms, and elements. New features of breath sampling and analysis are highlighted. Prospects and challenges on MS-based breath analysis related to COVID-19 diagnosis and study are discussed.

The snapshot of metabolic health in evaluating micronutrient status, the risk of infection and clinical outcome of COVID-19

COVID-19 has re-established the significance of analyzing the organism through a metabolic perspective to uncover the dynamic interconnections within the biological systems. The role of micronutrient status and metabolic health emerge as pivotal in COVID-19 pathogenesis and the immune system's response. Metabolic disruption, proceeding from modifiable factors, has been proposed as a significant risk factor accounting for infection susceptibility, disease severity and risk for post-COVID complications. Metabolomics, the comprehensive study and quantification of intermediates and products of metabolism, is a rapidly evolving field and a novel tool in biomarker discovery. In this article, we propose that leveraging insulin resistance biomarkers along with biomarkers of micronutrient deficiencies, will allow for a diagnostic window and provide functional therapeutic targets. Specifically, metabolomics can be applied as: a. At-home test to assess the risk of infection and propose nutritional support, b. A screening tool for high-risk COVID-19 patients to develop serious illness during hospital admission and prioritize medical support, c(i). A tool to match nutritional support with specific nutrient requirements for mildly ill patients to reduce the risk for hospitalization, and c(ii). for critically ill patients to reduce recovery time and risk of post-COVID complications, d. At-home test to monitor metabolic health and reduce post-COVID symptomatology. Metabolic rewiring offers potential virtues towards disease prevention, dissection of high-risk patients, taking actionable therapeutic measures, as well as shielding against post-COVID syndrome.

Could metabolomics drive the fate of COVID-19 pandemic? A narrative review on lights and shadows

Human Severe Acute Respiratory Syndrome CoronaVirus 2 (SARS-CoV-2) infection activates a complex interaction host/virus, leading to the reprogramming of the host metabolism aimed at the energy supply for viral replication. Alterations of the host metabolic homeostasis strongly influence the immune response to SARS-CoV-2, forming the basis of a wide range of outcomes, from the asymptomatic infection to the onset of COVID-19 and up to life-threatening acute respiratory distress syndrome, vascular dysfunction, multiple organ failure, and death. Deciphering the molecular mechanisms associated with the individual susceptibility to SARS-CoV-2 infection calls for a system biology approach; this strategy can address multiple goals, including which patients will respond effectively to the therapeutic treatment. The power of metabolomics lies in the ability to recognize endogenous and exogenous metabolites within a biological sample, measuring their concentration, and identifying perturbations of biochemical pathways associated with qualitative and quantitative metabolic changes. Over the last year, a limited number of metabolomics- and lipidomics-based clinical studies in COVID-19 patients have been published and are discussed in this review. Remarkable alterations in the lipid and amino acid metabolism depict the molecular phenotype of subjects infected by SARS-CoV-2; notably, structural and functional data on the lipids-virus interaction may open new perspectives on targeted therapeutic interventions. Several limitations affect most metabolomics-based studies, slowing the routine application of metabolomics. However, moving metabolomics from bench to bedside cannot imply the mere determination of a given metabolite panel; rather, slotting metabolomics into clinical practice requires the conversion of metabolic patient-specific data into actionable clinical applications.

Breast Milk and COVID-19: From Conventional Data to "Omics" Technologies to Investigate Changes Occurring in SARS-CoV-2 Positive Mothers

In this context of COVID-19 pandemic, great interest has been aroused by the potential maternal transmission of SARS-CoV-2 by transplacental route, during delivery, and, subsequently, through breastfeeding. Some open questions still remain, especially regarding the possibility of finding viable SARS-CoV-2 in breast milk (BM), although this is not considered a worrying route of transmission. However, in BM, it was pointed out the presence of antibodies against SARS-CoV-2 and other bioactive components that could protect the infant from infection. The aim of our narrative review is to report and discuss the available literature on the detection of anti-SARS-CoV-2 antibodies in BM of COVID-19 positive mothers, and we discussed the unique existing study investigating BM of SARS-CoV-2 positive mothers through metabolomics, and the evidence regarding microbiomics BM variation in COVID-19. Moreover, we tried to correlate metabolomics and microbiomics findings in BM of positive mothers with potential effects on breastfed infants metabolism and health. To our knowledge, this is the first review summarizing the current knowledge on SARS-CoV-2 effects on BM, resuming both "conventional data" (antibodies) and "omics technologies" (metabolomics and microbiomics).

COVID-19 and developmental origins of health and disease

From the moment of the identification of SARS-CoV-2 as an etiological agent of the severe clinical pictures of pneumonia that were being slowly observed all over the world, numerous studies have been conducted to increase the knowledge about what was an unknown virus until then. The efforts were mainly aimed to acquire epidemiological, microbiological, pathogenetic, clinical, diagnostic, therapeutic and preventive information in order to increase the available weapons to fight an infection which was rapidly taking on the characteristics of the pandemic. Given the topicality of the problem, not everything has yet been fully understood and clarified, especially in the maternal-fetal‑neonatal field, where we are beginning to question what could be the outcomes of newborn babies born to mothers who contracted SARS-CoV-2 infection during pregnancy. Thus, the aim of this review is to analyze the long-term outcomes of this infection that could affect the offspring, regardless of a possible maternal-fetal transmission, focusing on, above all, the role of maternal immune activation and the expression of the Angiotensin-converting enzyme 2 (ACE2) in particular at the placental level.

The Antiviral Properties of Human Milk: A Multitude of Defence Tools from Mother Nature

The anti-infective properties of breast milk have been known for decades. In recent years, an increasing number of papers have described the variety of bioactive compounds that are present in breast milk with varying degrees of antiviral activity. However, to date, the totality of the properties of these compounds is not fully understood and, above all, their synergistic interaction is not yet known. The purpose of this review is to describe the current knowledge about the antiviral compounds in breast milk, both with specific and non-specific action against pathogens. Due to the current pandemic situation from SARS-CoV-2 (Severe acute respiratory syndrome Coronavirus-2), research has focused on a multitude of potential antiviral substances, taking breast milk as a biological model of reference. Future research is needed to expand the knowledge of these compounds, which will hopefully assist in the development of therapies applicable even at later ages.

Comprehensive Meta-Analysis of COVID-19 Global Metabolomics Datasets

The novel coronavirus SARS-CoV-2 has spread across the world since 2019, causing a global pandemic. The pathogenesis of the viral infection and the associated clinical presentations depend primarily on host factors such as age and immunity, rather than the viral load or its genetic variations. A growing number of omics studies have been conducted to characterize the host immune and metabolic responses underlying the disease progression. Meta-analyses of these datasets have great potential to identify robust molecular signatures to inform clinical care and to facilitate therapeutics development. In this study, we performed a comprehensive meta-analysis of publicly available global metabolomics datasets obtained from three countries (United States, China and Brazil). To overcome high heterogeneity inherent in these datasets, we have (a) implemented a computational pipeline to perform consistent raw spectra processing; (b) conducted meta-analyses at pathway levels instead of individual feature levels; and (c) performed visual data mining on consistent patterns of change between disease severities for individual studies. Our analyses have yielded several key metabolic signatures characterizing disease progression and clinical outcomes. Their biological interpretations were discussed within the context of the current literature. To the best of our knowledge, this is the first comprehensive meta-analysis of global metabolomics datasets of COVID-19.