Tag Archives: Biomarker

Microbiology

University of Louisville researchers receive $5.8 million to prevent immune system dysregulation

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Reviewed by Megan Craig, M.Sc.Jun 2 2023

Researchers at the University of Louisville have received $5.8 million in two grants from the National Institutes of Health to expand their work to better understand and prevent immune system dysregulation responsible for acute respiratory distress, the condition responsible for serious illness and death in some COVID-19 patients. A separate $306,000 NIH Small Business Innovation Research grant supports early testing of a compound developed at UofL as a potential treatment.

The three grants combined total $6.1 million.

During the pandemic, health care providers worked tirelessly to treat patients who became seriously ill with COVID-19. Some of those patients developed severe lung disease known as acute respiratory distress syndrome (ARDS) due to an excessive response of the immune system often called cytokine storm.

As they treated these critically ill patients, physicians and other providers at UofL Health shared their clinical insights and patient samples with researchers at UofL to discover the cause of the immune system overresponse.

At one time we had over 100 patients with COVID in the hospital. Once they were on a ventilator, mortality was about 50%. We were looking at this issue to see why some people would do well while some developed bad lung disease and did not do well or died.”

Jiapeng Huang, an anesthesiologist with UofL Health and professor and vice chair of the Department of Anesthesiology and Perioperative Medicine in the UofL School of Medicine

The UofL researchers, led by immunologist Jun Yan, discovered that a specific type of immune cells, low-density inflammatory neutrophils, became highly elevated in some COVID-19 patients whose condition became very severe. This elevation signaled a clinical crisis point and increased likelihood of death within a few days due to lung inflammation, blood clotting and stroke. Their findings were published in 2021 in JCI Insight.

With the new NIH funding, Yan is leading research to build on this discovery with deeper understanding of what causes a patient’s immune system to respond to an infection in this way and develop methods to predict, prevent or control the response.

“Through this fruitful collaboration, we now have acquired NIH funding for basic and translational studies and even progress toward commercialization of a potential therapy,” Yan said. “That’s why we do this research – eventually we want to benefit the patients.”

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Yan, chief of the UofL Division of Immunotherapy in the Department of Surgery, a professor of microbiology and immunology and a senior member of the Brown Cancer Center, will lead the new research, along with Huang and Silvia M. Uriarte, university scholar and professor in the Department of Oral Immunology and Infectious Diseases in the UofL School of Dentistry.

“COVID-19 continues to spotlight the impactful synergy between the clinical and research teams at the University of Louisville,” said Jason Smith, UofL Health chief medical officer. “Innovation is in the DNA of academic medicine. We collaborate to provide each patient the best options for prevention and treatment today, while developing the even better options for tomorrow.”

In addition to two research grants of $2.9 million each awarded directly to UofL, a $306,000 grant to a startup company will support early testing of a compound developed in the lab of UofL Professor of Medicine Kenneth McLeish that shows promise in preventing the dangerous cytokine storm while allowing the neutrophils to retain their ability to kill harmful bacteria and viruses. The compound, DGN-23, will be tested by UofL and Degranin Therapeutics, a startup operated by McLeish, Yan, Huang, Uriarte and Madhavi Rane, associate professor in the Department of Medicine.

“This is one more example of how UofL has led the charge in finding new and innovative ways to detect, contain and fight COVID-19 and other potential public health threats,” said Kevin Gardner, UofL’s executive vice president for research and innovation. “This team’s new research and technology could help keep people healthy and safe here and beyond.”

The knowledge gained through these studies may benefit not only COVID-19 patients, but those with other conditions in which immune dysregulation can occur, such as other types of viral and bacterial pneumonia and autoimmune diseases, and patients undergoing cancer immunotherapy and organ transplantation.

The grants

Grant 1 – $2.9 million, four-year grant to UofL. Investigators will study the new subset of neutrophils Yan identified to better understand how they contribute to acute respiratory distress and clotting. They also will determine whether a novel compound will prevent these complications. They will use lab techniques and studies with animal models that allow for manipulation of certain conditions that cannot be done in human subjects.

Grant 2 – $2.9 million, five-year grant to UofL. This work examines a more comprehensive landscape to characterize different subsets of neutrophils and measure their changes over the course of COVID-19 disease progression and how neutrophils contribute to immune dysfunction.

Grant 3 – $306,000, one-year grant to Degranin Therapeutics and UofL for early testing of DGN-23, a compound developed at UofL, to determine its effectiveness in preventing or reducing immune dysregulation.

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Source:

University of Louisville

Microbiology

Novel subset of memory B cells predicts long-lived antibody responses to influenza vaccination

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Reviewed by Emily Henderson, B.Sc.Mar 22 2023

Memory B cells play a critical role to provide long-term immunity after a vaccination or infection. In a study published in the journal Immunity, researchers describe a distinct and novel subset of memory B cells that predict long-lived antibody responses to influenza vaccination in humans.

These effector memory B cells appear to be poised for a rapid serum antibody response upon secondary challenge one year later, Anoma Nellore, M.D., Fran Lund, Ph.D., and colleagues at the University of Alabama at Birmingham and Emory University report. Evidence from transcriptional and epigenetic profiling shows that the cells in this subset differ from all previously described memory B cell subsets.

The UAB researchers identified the novel subset by the presence of FcRL5 receptor protein on the cell surface. In immunology, a profusion of different cell-surface markers is used to identify and separate immune-cell types. In the novel memory B cell subset, FcRL5 acts as a surrogate marker for positive expression of the T-bet transcription factor inside the cells. Various transcription factors act as master regulators to orchestrate the expression of many different gene sets as various cell types grow and differentiate.

Nellore, Lund and colleagues found that the FcRL5+ T-bet+ memory B cells can be detected seven days after immunization, and the presence of these cells correlates with vaccine antibody responses months later. Thus, these cells may represent an early, easily monitored cellular compartment that can predict the development of a long-lived antibody response to vaccines.

This could be a boon to the development of a more effective yearly influenza vaccine. “New annual influenza vaccines must be tested, and then manufactured, months in advance of the winter flu season,” Lund said. “This means we must make an educated guess as to which flu strain will be circulating the next winter.”

Why are vaccine candidates made so far in advance? Pharmaceutical companies, Lund says, need to wait many weeks after vaccinating volunteers to learn whether the new vaccine elicits a durable immune response that will last for months. “One potential outcome of the current study is we may have identified a new way to predict influenza vaccine durability that would give us an answer in days, rather than weeks or months,” Lund said. “If so, this type of early ‘biomarker’ could be used to test flu vaccines closer to flu season -; and moving that timeline might give us a better shot at predicting the right flu strain for the new annual vaccine.”

Seasonal flu kills 290,000 to 650,000 people each year, according to World Health Organization estimates. The global flu vaccine market was more than $5 billion in 2020.

To understand the Immunity study, it is useful to remember what happens when a vaccinated person subsequently encounters a flu virus.

Following exposure to previously encountered antigens, such as the hemagglutinin on inactivated influenza in flu vaccines, the immune system launches a recall response dominated by pre-existing memory B cells that can either produce new daughter cells or cells that can rapidly proliferate and differentiate into short-lived plasmablasts that produce antibodies to decrease morbidity and mortality. These latter B cells are called “effector” memory B cells.

“The best vaccines induce the formation of long-lived plasma cells and memory B cells,” said Lund, the Charles H. McCauley Professor in the UAB Department of Microbiology and director of the Immunology Institute. “Plasma cells live in your bone marrow and make protective antibodies that can be found in your blood, while memory B cells live for many years in your lymph nodes and in tissues like your lungs.

“Although plasma cells can survive for decades after vaccines like the measles vaccine, other plasma cells wane much more quickly after vaccination, as is seen with COVID-19,” Lund said. “If that happens, memory B cells become very important because these long-lived cells can rapidly respond to infection and can quickly begin making antibody.”

In the study, the UAB researchers looked at B cells isolated from blood of human volunteers who received flu vaccines over a span of three years, as well as B cells from tonsil tissue obtained after tonsillectomies.

They compared naïve B cells, FcRL5+ T-bet+ hemagglutinin-specific memory B cells, FcRL5neg T-betneg hemagglutinin-specific memory B cells and antibody secreting B cells, using standard phenotype profiling and single-cell RNA sequencing. They found that the FcRL5+ T-bet+ hemagglutinin-specific memory B cells were transcriptionally similar to effector-like memory cells, while the FcRL5neg T-betneg hemagglutinin-specific memory B cells exhibited stem-like central memory properties.

Antibody-secreting B cells need to produce a lot of energy to churn out antibody production, and they also must turn on processes that protect the cells from some of the detrimental side effects of that intense metabolism, including controlling the dangerous reactive oxygen species and boosting the unfolded protein response.

The FcRL5+ T-bet+ hemagglutinin-specific memory B cells did not express the plasma cell commitment factor, but did express transcriptional, epigenetic and metabolic functional programs that poised these cells for antibody production. These included upregulated genes for energy-intensive metabolic processes and cellular stress responses.

Accordingly, FcRL5+ T-bet+ hemagglutinin-specific memory B cells at Day 7 post-vaccination expressed intracellular immunoglobulin, a sign of early transition to antibody-secreting cells. Furthermore, human tonsil-derived FcRL5+ T-bet+ memory B differentiated more rapidly into antibody-secreting cells in vitro than did FcRL5neg T-betneg hemagglutinin-specific memory B cells.

Lund and Nellore, an associate professor in the UAB Department of Medicine Division of Infectious Diseases, are co-corresponding authors of the study, “A transcriptionally distinct subset of influenza-specific effector memory B cells predicts long-lived antibody responses to vaccination in humans.”

Co-authors with Lund and Nellore are Esther Zumaquero, R. Glenn King, Betty Mousseau, Fen Zhou and Alexander F. Rosenberg, UAB Department of Microbiology; Christopher D. Scharer, Tian Mi, Jeremy M. Boss, Christopher M. Tipton and Ignacio Sanz, Emory University School of Medicine, Atlanta, Georgia; Christopher F. Fucile, UAB Informatics Institute; John E. Bradley and Troy D. Randall, UAB Department of Medicine, Division of Clinical Immunology and Rheumatology; and Stuti Mutneja and Paul A. Goepfert, UAB Department of Medicine Division of Infectious Diseases.

Funding for the work came from National Institutes of Health grants AI125180, AI109962 and AI142737 and from the UAB Center for Clinical and Translational Science.

Source:

University of Alabama at Birmingham

Journal reference:

Nellore, A., et al. (2023). A transcriptionally distinct subset of influenza-specific effector memory B cells predicts long-lived antibody responses to vaccination in humans. Immunity. doi.org/10.1016/j.immuni.2023.03.001.

Microbiology

Review on factors related to variations in human microbiota

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Pooja Toshniwal PahariaBy Pooja Toshniwal PahariaMar 8 2023Reviewed by Aimee Molineux

In a recent review published in Current Opinion in Microbiology, researchers reviewed existing data on variations in human microbiota, emphasizing on ageing- and ethnicity-associated changes in the microbiota.

Study: Human microbiome variance is underestimated. Image Credit: Troyan/Shutterstock
Study: Human microbiome variance is underestimated. Image Credit: Troyan/Shutterstock

Background

Human microbial heterogeneity lays the foundation for precision therapeutics, and thus, the potential of personalized microbiota-based diagnostic and therapeutic strategies can be tapped fully by understanding human microbial variations. However, the factors associated with alterations in the human microbiome have yet to be well-characterized.

Further, most of the human microbiota data has been obtained from residents of westernized and socioeconomically developed nations, with the probable skewing of microbiota variations and their associations with health. Moreover, the under-sampling of ethnic minorities in microbiota analyses must be addressed for assessing the history, context, and evolving dynamics of the human microbiota in the context of disease risks.

About the review

In the present review, researchers highlighted recent advances in characterizing human microbiota variations associated with ageing and various ethnicities globally.

Age-related changes in the microbiota of humans

Factors that shape the human microbiota include birth type, family sizes, cohabitation, housing, domestic animals, age, sex, physical fitness, diet, antibiotics, non-antibiotic drugs, and alcohol intake. At the societal level, complex associations of health inequalities, socioeconomic status, and social networks with the human microbiome balance have been reported.

Studies have demonstrated an inverse association between the microbiota and an individual’s age, and conversely, microbial compositional variations contribute to the process of ageing and age-associated diseases. All individuals do not age uniformly, and the differential ageing rates reflect in the human microbiota. Therefore, the human microbiota abundance is evolving as a biomarker to evaluate differences in the biological age and chronological age and between health and disease. Human microbiomes lacking Bacteroides species have been strongly associated with a healthy type of ageing.

Other factors related to variations in the human microbiota composition

Mediterranean diets, involving reduced intake of saturated-type fats, red meat, and milk products, with high consumption of fruits, vegetables, fish, legumes, nuts, and olive oil, have been reported to reverse age-associated microbiota alterations and delay cognitive decline. Studies have reported the co-evolution of human beings and intestinal microbes, with notable variations in Helicobacter pylori diversity associated with human migration.

Microbiome compositions vary among individuals residing in industrialized or non-industrialized regions. Non-industrialized region-associated microbiomes or ancestral microbes have adapted to metabolizing complex-type carbohydrates from diets with high fibre content. The microbial compositions vary by season, climatic fluctuations, and accessibility to unprocessed-type foods. The microbiome of individuals living in non-industrialized regions reportedly has lower Bacteroides/Prevotella spp. ratio, elevated counts of Treponema species, and varying abundance of parasites that affect the immunity of the host.

Naturally maintained palaeofaeces microbiome genomes resemble the genomes of non-industrialized human intestinal microbiota. Socioeconomic developments and industrialization have been associated with microbiome diversity losses, lowered parasitism, reduced counts of ancestral microbes like Helicobacter pylori species and elevated counts of microbes associated with non-communicable and chronic metabolic and inflammatory diseases.

Immigration has been related to an increased abundance of microbes associated with obesity. A study on Irish travellers reported three key factors influencing the human microbiota composition, i.e., living conditions, closeness to domestic pets during childhood and family sizes, with the average number of siblings among traveller families and other families being 10, and one, respectively).

Conclusions

Based on the review findings, the human microbiome is influenced by age, diet, ethnicity and immigration. Further research is required to improve understanding of age-related microbiome changes to identify targets and develop tailored microbiota-based therapeutic interventions. The increase or decrease in microbial abundance associated with changes in dietary patterns and modernization needs to be assessed further to develop highly specific precision medicine catered to the residential locations and food consumed.

The co-diversification of microbes with humans globally warrants in-depth analysis of microbial compositions by ethnicity, region, diet, and industrialization status to maximize the benefit of microbiota-based interventions to one and all. Microbial analyses were performed to evaluate the risk of disease in relation to microbiome dysbiosis and abrupt changes following immigration could inform policy-makers and decision-making and aid in developing personalized therapeutics to improve the standard of care for all individuals across the globe.

Journal reference:
Microbiology

Simple blood tests for telomeric protein could provide a valuable screen for certain cancers

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Reviewed by Emily Henderson, B.Sc.Feb 21 2023

Once thought incapable of encoding proteins due to their simple monotonous repetitions of DNA, tiny telomeres at the tips of our chromosomes seem to hold a potent biological function that’s potentially relevant to our understanding of cancer and aging.

Reporting in the Proceedings of the National Academy of Science, UNC School of Medicine researchers Taghreed Al-Turki, PhD, and Jack Griffith, PhD, made the stunning discovery that telomeres contain genetic information to produce two small proteins, one of which they found is elevated in some human cancer cells, as well as cells from patients suffering from telomere-related defects.

Based on our research, we think simple blood tests for these proteins could provide a valuable screen for certain cancers and other human diseases. These tests also could provide a measure of ‘telomere health,’ because we know telomeres shorten with age.”

Jack Griffith, PhD, the Kenan Distinguished Professor of Microbiology and Immunology and Member of the UNC Lineberger Comprehensive Cancer Center

Telomeres contain a unique DNA sequence consisting of endless repeats of TTAGGG bases that somehow inhibit chromosomes from sticking to each other. Two decades ago, the Griffith laboratory showed that the end of a telomere’s DNA loops back on itself to form a tiny circle, thus hiding the end and blocking chromosome-to-chromosome fusions. When cells divide, telomeres shorten, eventually becoming so short that the cell can no longer divide properly, leading to cell death.

Scientist first identified telomeres about 80 years ago, and because of their monotonous sequence, the established dogma in the field held that telomeres could not encode for any proteins, let alone ones with potent biological function.

In 2011 a group in Florida working on an inherited form of ALS reported that the culprit was an RNA molecule containing a six-base repeat which by a novel mechanism could generate a series of toxic proteins consisting of two amino acids repeating one after the other. Al-Turki and Griffith note in their paper a striking similarity of this RNA to the RNA generated from human telomeres, and they hypothesized that the same novel mechanism might be in play.

They conducted experiments – as described in the PNAS paper – to show how telomeric DNA can instruct the cell to produce signaling proteins they termed VR (valine-arginine) and GL (glycine-leucine). Signaling proteins are essentially chemicals that trigger a chain reaction of other proteins inside cells that then lead to a biological function important for health or disease.

Al-Turki and Griffith then chemically synthesized VR and GL to examine their properties using powerful electron and confocal microscopes along with state-of-the-art biological methods, revealing that the VR protein is present in elevated amounts in some human cancer cells, as well as cells from patients suffering from diseases resulting from defective telomeres.

“We think it’s possible that as we age, the amount of VR and GL in our blood will steadily rise, potentially providing a new biomarker for biological age as contrasted to chronological age,” said Al-Turki, a postdoctoral researcher in the Griffith lab. “We think inflammation may also trigger the production of these proteins.”

Griffith noted, “When you go against current thinking, you are usually wrong because you are bucking many people who’ve worked so diligently in their fields. But occasionally scientists have failed to put observations from two very distant fields together and that’s what we did. Discovering that telomeres encode two novel signaling proteins will change our understanding of cancer, aging, and how cells communicate with other cells.

“Many questions remain to be answered, but our biggest priority now is developing a simple blood test for these proteins. This could inform us of our biological age and also provide warnings of issues, such as cancer or inflammation.”

Source:

University of North Carolina Health Care

Journal reference:

Al-Turki, T., et al. (2023) Mammalian Telomeric RNA (TERRA) can be translated to produce valine-arginine and glycine-leucine dipeptide repeat proteins. PNAS. doi.org/10.1073/pnas.2221529120.

Microbiology

What are the major findings of long COVID research?

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Pooja Toshniwal PahariaBy Pooja Toshniwal PahariaJan 17 2023Reviewed by Aimee Molineux

In a recent review published in Nature Reviews Microbiology, researchers explored existing literature on long coronavirus disease (COVID). They highlighted key immunological findings, similarities with other diseases, symptoms, associated pathophysiological mechanisms, and diagnostic and therapeutic options, including coronavirus disease 2019 (COVID-19) vaccinations.

Study: Long COVID: major findings, mechanisms and recommendations. Image Credit: Ralf Liebhold/Shutterstock
Study: Long COVID: major findings, mechanisms and recommendations. Image Credit: Ralf Liebhold/Shutterstock

Long COVID refers to a multisystemic disease among SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2)-positive individuals, with increasing prevalence rates by the day. Studies have reported on long COVID risk factors, symptoms, pathophysiology, diagnosis, and treatment options, with increasing similarities between long COVID and other diseases such as POTS (postural orthostatic tachycardia syndrome) and ME/CFS (myalgic encephalomyelitis/ chronic fatigue syndrome).

About the review

In the present review, researchers explored the existing data on long COVID immunology, symptoms, pathophysiology, diagnosis, and therapeutic options.

Key long COVID findings and similarities with other diseases

Studies have reported persistently reduced exhausted T lymphocytes, dendritic cells, cluster of differentiation 4+ (CD4+) lymphocyte and CD8+ lymphocyte counts, and greater PD1 (programmed cell death protein-1) expression. In addition, increase in innate cell immunological activities, non-classical monocytes, expression of interferons (IFNs)-β, λ1, and interleukins (IL)-1β, 4,6, tumor necrosis factor (TNF). Cytotoxic T lymphocyte expansion has been linked to gastrointestinal long COVID symptoms, and persistent increase in CCL11 (C-X-C motif chemokine 11) expression has been linked to cognitive dysfunction among long COVID patients.

Elevated autoantibody titers have been reported among long COVID patients, such as autoantibodies against ACE2 (angiotensin-converting enzyme 2), angiotensin II receptor type I (AT1) receptors, β2-adrenoceptors, angiotensin 1–7 Mas receptors, and muscarinic M2 receptors. Reactivation of Epstein-Barr virus (EBV) and human herpes virus-6 (HHV-6) has been reported in long COVID patients and ME/CFS. EBV reactivation has been linked to neurocognitive impairments and fatigue in long COVID.

SARS-CoV-2 persistence reportedly drives long COVID symptoms. SARS-CoV-2 proteins and/or ribonucleic acid (RNA) have been detected in cardiovascular, reproductive, cranial, ophthalmic, muscular, lymphoid, hepatic, and pulmonary tissues, and serum, breast, urine, and stool obtained from long COVID patients. Similar immunological patterns are noted between long COVID and ME/CFS, with elevated cytokine levels in the initial two to three years of disease, followed by reduction with time, without symptomatic improvements in ME/CFS. Lower cortisol levels, mitochondrial dysfunction, post-exertional malaise, dysautonomia, mast cell activation, platelet hyperactivation, hypermobility, endometriosis, menstrual alterations, and intestinal dysbiosis occur in both conditions.

Long COVID symptoms and underlying pathophysiological mechanisms

Long COVID-associated organ damage reportedly results from COVID-19-induced inflammation and associated immune responses. Cardiovascular long COVID symptoms such as chest pain and palpitations have been associated with endothelial dysfunction, micro-clotting, and lowered vascular density. Long COVID has been associated with an increased risk of renal damage and type 2 diabetes. Ophthalmic symptoms of long COVID, including altered pupillary responses to light, result from the loss of small nerve fibers in the cornea, increased dendritic cell density, and impaired retinal microvasculature. Respiratory symptoms such as persistent cough and breathlessness result from altered pulmonary perfusion, epithelial injury, and air entrapment in the airways.

Cognitive and neurological long COVID symptoms include loss of memory, cognitive decline, sleep difficulties, paresthesia, balancing difficulties, noise and light sensitivity, tinnitus, and taste and/or smell loss. Underlying pathophysiological mechanisms include kynurenine pathway activation, endothelial injury, coagulopathy, lower cortisol levels, loss of myelin, microglial reactivation, oxidative stress, hypoxia, and tetrahydrobiopterin deficiency.  Gastrointestinal symptoms such as pain in the abdomen, nausea, appetite loss, constipation, and heartburn have been associated with elevated Bacteroides vulgatus and Ruminococcus gnavus counts and lower Faecalibacterium prausnitzii counts. Neurological symptoms often have a delayed onset, worsen with time and persist longer than respiratory and gastrointestinal symptoms, and long COVID presents similarly in children and adults.

Diagnostic and therapeutic options for long COVID, including COVID-19 vaccines

The diagnosis and treatment of long COVID are largely symptom-based, including tilt tests for POTS, magnetic resonance imaging (MRI) to detect cardiovascular and pulmonary impairments, and electrocardiograms to detect QRS complex fragmentation. Salivary tests and serological tests, including red blood cell deformation, lipid profile, complete blood count, D-dimer, and C-reactive protein (CRP) evaluations, can be performed to assess immunological biomarker levels. PCR (polymerase chain reaction) analysis is used for SARS-CoV-2 RNA detection and quantification, and antibody testing is performed to assess humoral immune responses against SARS-CoV-2.

Pharmacological treatments include intravenous Ig for immune dysfunction, low-dosage naltrexone for neuronal inflammation, beta-blockers for POTS, anticoagulants for microclot formation, and stellate ganglion blockade for dysautonomia. Other options include antihistamines, paxlovid, sulodexide, and pycnogenol. Non-pharmacological options include cognitive pacing for cognitive impairments, diet limitations for gastrointestinal symptoms, and increasing salt consumption for POTS. COVID-19 vaccines have conferred minimal protection against long COVID, the development of which depends on the causative SARS-CoV-2 variant, and the number of vaccination doses received. Long COVID has been reported more commonly post-SARS-CoV-2 Omicron BA.2 subvariant infections.

Based on the review findings, long COVID is a multiorgan disease that has debilitated several lives worldwide, for which diagnostic and therapeutic options are inadequate. The findings underscored the need for future studies, clinical trials, improved education, mass communication campaigns, policies, and funding to reduce the future burden of long COVID.

Journal reference:
Microbiology

The vaginal microbiome through the lens of systems biology

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Dr. Liji Thomas, MDBy Dr. Liji Thomas, MDNov 22 2022Reviewed by Emily Henderson, B.Sc.

The human organism is a complex ecosystem of coexisting microbiomes, including those in the gut, the skin, and the vagina in females. These play a crucial role in health and disease. However, a great deal remains to be learned about them.

A new paper recently published online in Trends in Microbiology journal reviews the systems biology approach to explore the vaginal microbiome (VMB), helping to understand its composition and function and the mechanisms by which it interacts with the host.

Review: New perspectives into the vaginal microbiome with systems biology. Image Credit: Design_Cells / ShutterstockReview: New perspectives into the vaginal microbiome with systems biology. Image Credit: Design_Cells / Shutterstock

Introduction

The VMB is vital in female fertility, and disruptions can be associated with pregnancy disorders, gynecologic diseases such as pelvic inflammatory disease (PID), and an array of infections involving the female genitourinary and reproductive tract. In addition, the VMB may be instrumental in affecting drug efficacy in women.  

However, the VMB is little understood beyond a vague idea that a preponderance of Lactobacillus is associated with a ‘good’ state with a homogeneous community structure. Conversely, an undesirable state of the VMB exists when more diverse species are identified in greater abundance.

This latter suboptimal state is often linked to bacterial vaginosis (BV), found in one in three women during their reproductive period, which can have severe consequences on their fertility. As such, research in this area is required to understand the directionality and magnitude of such associations.

The problem

While many studies have been performed in this area, it is difficult to understand what an optimal VMB looks like because of the complex interactions between microbes and other host factors. This means that the healthy VMB can differ considerably from woman to woman and at different points in the same individual’s life cycle.

Such changes occur within days, which contrasts with the much slower shift seen with the gut, skin, and oral microbiomes, which may change over months or even years. Unfortunately, this makes cross-sectional data quite non-representative when it comes to studying the association of VMB composition, function, and disease – and thus makes most of this data less useful than it could be.

Again, the human VMB differs significantly from that of animals, as well as from culture-based models. In the former, even non-human primates fail to show the characteristic conditions of the human vagina, including the acidic pH and Lactobacillus dominance.

In the latter, some microbes are incredibly resistant to culture in vitro, while various culture conditions are used in different laboratories, depending on the media. This could make the growth environment quite different from that of the human cervix and vagina, invalidating the results of such experiments.

As such, clinical samples from which vaginal microflora are cultured, identified, and quantified form the primary source of information about the human VMB. This information is colored by experimental and host variables, which require sophisticated statistical adaptations to achieve a valid conclusion.

“While relevant to all microbiome sites, [this] is particularly applicable to the VMB because of its lack of experimental models that allow for interrogation of vaginal microbiota under controlled conditions.”

The solution

Such an impasse can be solved with a systems biology approach, where quantitative analyses are used to extract the important factors affecting the behavior and function of a microbial community. As such, “Leveraging systems biology techniques applied to other microbiomes, as well as developing novel techniques and applying these methods to the VMB, will have a significant impact on improving women’s health.”

The use of systems biology can overcome the challenges of such complex and multiple external and internal interactive networks. Furthermore, multiple approaches can be used, depending on the type of information available and the aim of the study.

Thus, statistical or data-driven methods are ideal when high-throughput data are abundant in a relatively new field of study. This can help suggest what microbial profiles are linked to disease or health. Since little is known so far about the VMB, data-driven models have predominated so far.

Conversely, based on hypotheses, mechanistic methods are better when much is already known about a system, or at least the fundamental data is available, and the need is to understand the mechanisms of cause-effect associations underlying biological function. In addition, they help to set the ranges within which microbial composition and interactions can occur in normal and abnormal situations.

Some mechanistic methods include mass-action kinetic or population dynamics models (based on differential equations), genome-scale metabolic models (GEMs), and agent-based models (ABMs).

What has been achieved?

The systems biology approach has already helped to identify and categorize community state types (CSTs) associated with health, disease, or transitions between the two. First defined by microbial abundance, they incorporated patient demographic and health data to form hierarchical clustering groups. In addition, other methods like nearest centroid classification have been developed to overcome the inherent variation in the dataset with the former approach.

CST groupings help simplify VMB composition and thus suggest associations with community composition and function. But this is at the cost of overlooking community-specific factors specific to different taxa.

Multi-omics approaches could be integrated with systems biology strategies to identify associations with different types of community and specific metabolomics, transcriptomics, and metagenomics profiles, for instance. In addition, random forest models and other advanced machine learning models are being pressed into service to help distinguish VMBs with a predominance of different microbes, such as L. crispatus vs. L. iners or Bifidobacteriaceae.

Interestingly, neural network models have shown the superiority of metabolomics in describing the cervicovaginal environment accurately compared to either VMB composition or immunoproteomics. The integrated use of these strategies could help pick out the important drivers of VMB states in health and disease.

Especially important could be the insights obtained regarding sexually transmitted infection (STI) risk with an increased abundance of ‘bad’ microbes. For instance, an increase in L. iners seems to be associated with a higher risk for STIs, while L. gasseri is associated with health. Conversely, Gardnerella vaginalis and Prevotella species are linked to Chlamydia infection.

Mechanistic models include the technique called MIMOSA (Model-based Integration of Metabolite Observations and Species Abundances) that uses metabolic network modeling to understand community function via its gene content. This helped identify Prevotella species and Atopobium vaginae as key modulators of the VMB, using a calculated community-based metabolite potential (CMP) score. The CMP shows the turnover of each metabolite by any given community.

Similarly, genome-scale network reconstructions (GENREs) could help understand the role of fastidious microbes in the VMB. Ordinary differential equation (ODE)-based models are being used to examine how drugs can affect the VMB and the ecology of this system, showing how the composition fluctuates following exposure to different factors.

What lies in the future?

A multitude of studies has focused on the gut microbiome, with almost $150 million being poured into developing and standardizing new tools for its exploration. VMB researchers may be able to use these to serve their aims. This includes BURRITO, a web tool that helps visualize a microbiome community by relative abundance. This could be extended to examine VMB metagenomics, showing how patient symptoms relate to the CSTs.

Supervised machine learning approaches to understand the VMB better include Data Integration Analysis for Biomarker Discovery using Latent cOmponents (DIABLO), where omics datasets are integrated by correlation, and Sparse regularized generalized canonical correlation analysis (SRGCCA), used in Crohn’s disease.

To overcome the limitations imposed by the lack of knowledge about the functional classification of the VMB, unsupervised learning strategies may be useful, such as multi-omic factor analysis (MOFA).

Many ODE models can also be used based on the Generalized Lotka–Volterra (gLV) models. These include web-gLV, Microbial dynamical systems inference engine for microbiome time-series analysis (MDSINE), and the learning interactions from microbial time series (LIMITS) method, as well as newer adaptations like the compositional Lotka–Volterra (cLV) and the ‘Biomass Estimation and Model Inference with an Expectation Maximization’ algorithm (BEEM), that are not dependent on the culturability of the community or on the availability of extensive longitudinal datasets.

Newer methods include algorithms like Constant yield expectation framework (conYE) and MMinte, that simulate conditions for community metabolism and growth based on dense interactions between the species. Such ingenious adaptations and approaches could help understand the factors that shape the dynamic VMB in health and disease in different populations.

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