Tag Archives: Dysbiosis

Smoking alters lung microbiome, leading to loss of diversity and community structure

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In a recent study published in the journal Access Microbiology, researchers explore the composition of the microbiome and interactions in the lower respiratory tract (LRT) in smokers. 

Study: Lower respiratory tract microbiome composition and community interactions in smokers. Image Credit: vchal / Shutterstock.com

The impact of smoking on the respiratory microbiome

Smoking has been shown to impact resident microbial communities present in different bodily regions. Previous studies have proposed various mechanisms responsible for this association, such as immunosuppression related to smoking, an increase in biofilm formation for specific species, and selection of species by the influence of local oxygen tension.

The upper airways and oral cavities may also directly interact with smoking chemicals, microbes, and heat from cigarettes, which can alter microbiome content. Recent studies have hypothesized that dysbiosis noted in the oral microbiome related to smoking may lead to a greater likelihood of experiencing complications in the respiratory tract among smokers. 

About the study

In the present study, researchers compare the LRT microbiome profiles of active smokers (AS), former smokers (FS), and non-smokers (NS) to describe the bacterial communities present in the lung.

The study involved volunteer subjects aged over 40 years of age who were either smokers of a minimum of 10 pack-years throughout their life or non-smokers. Former smokers qualified for the study if they had abstained from using tobacco for a minimum of 12 months, while AS smoked a minimum of one cigarette within three days of recruitment.

All study participants were required to complete a pulmonary function examination and thorough demographic and clinical questionnaire. The sampling process was standardized for all participants. The team extracted total deoxyribonucleic acid (DNA) from the bronchoalveolar lavages (BALs) specimens.

A single polymerase chain reaction (PCR) assessment was conducted to amplify the V6-V8 region present on the 16S ribosomal ribonucleic acid (rRNA) gene from the metagenomic DNA extracts of the BAL samples. Alpha diversity was estimated using Chao richness and inverse Simpson diversity indices. The DESeq2 algorithm was also used to detect differentiating taxa for each cohort.

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Study findings

All 46 smokers reported similar smoking exposure in terms of pack-years, including the FS quitting smoking on an average of about 10 years prior to enrollment. AS and FS exhibited reduced forced vital capacity (FVC), diffusing capacity for carbon monoxide (DL-CO), and forced expiratory volume at second 1 (FEV1); however, these variations were not remarkable according to the analysis of variance (ANOVA).

Over 3,600 reads with an average length of about 479 nucleotides were documented in each participant’s BAL, which facilitated the description of almost 400 operational taxonomic units (OTUs) per participant. The NS profile was sufficiently balanced between the prevalent phyla Bacteroides, Firmicutes, Proteobacteria, and Actinobacteria with comparatively slightly higher proportions. The FS cohort had a significant increase in Proteobacteria with reduced Bacteroides and Firmicutes levels. This pattern was also true for AS, with Proteobacteria increasing to 75% and Firmicutes declining to 11%.

Genus-level assessments indicated that most of the enhancement in Proteobacteria in AS and FS in comparison to its high proportion in NS was due to the genus Ralstonia, which increased from 2% in the NS, 28% in AS, and 21% in FS.

From the Firmicutes phylum, the Streptococcus and Veillonella genera, as well as Prevotella from the Bacteroidetes phyla exhibited the greatest decline in comparative abundance. Furthermore, the Propionibacterium genus of the Actinobacteria phylum exhibited a slight improvement from 3% in AS and FS to 0.8% in NS.

With respect to the NS profile, a greater number of upper-quartile taxa were distinguished from AS, whereas lower-quartile taxa were distinguished from FS.

NS exhibited a considerably higher mean diversity as compared to AS and FS. The mean diversity further increased when the participants were placed by declining richness, thus indicating that NS reported higher richness. Yet, the diversity evaluated with the inverse Simpson index had only an intermediate association with richness estimates and the participant’s smoking status.

Conclusions

The current study provides new insights into the complicated microbial communities found in the LRT and how this microbiome can be changed under different smoking conditions. The researchers also observed that the oral microbiota can settle in the lungs of smokers, which makes the study of the upper airway microbiome interesting for future research.

The microbiomes of former smokers appear to exhibit similar properties to those of both AS and NS. In the future, integration of the present findings with next-generation analytical techniques would help establish the effect of such microbial communities on human health.

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Journal reference:
  • Campos, M., Cickovski, T., Fernandez, M., et al. (2023). Lower respiratory tract microbiome composition and community interactions in smokers. Access Microbiology. doi:10.1099/acmi.0.000497.v3

Can a disrupted gut microbiota contribute to anorexia nervosa pathogenesis?

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In a recent study published in the journal Nature Microbiology, researchers investigated whether intestinal microbial alterations contribute to anorexia nervosa (AN) pathogenesis.

AN, a disorder associated with altered eating, has caused considerable mortality, especially among women. However, therapies based on scientific evidence are scarce. AN pathogenesis likely involves several environmental and genetic factors. Studies have reported intestinal microbial dysbiosis among AN-affected individuals. However, data were obtained from small sample sizes, and genus-level microbial alterations were analyzed by amplicon sequencing.

Study: The gut microbiota contributes to the pathogenesis of anorexia nervosa in humans and mice. Image Credit: Tatiana Shepeleva / ShutterstockStudy: The gut microbiota contributes to the pathogenesis of anorexia nervosa in humans and mice. Image Credit: Tatiana Shepeleva / Shutterstock

About the study

In the present study, researchers assessed the association between the intestinal microbiome and AN.

The team performed metabolomics and shotgun metagenomic analyses on serum and fecal samples, respectively, that were obtained from women with AN (n=77) and age- and sex-matched healthy controls (n=70). Further, the fecal microbiome was transplanted from anorexia nervosa cases to murine animals fed calories-limited diets over three weeks to simulate AN eating behavior for in vivo analysis. In addition, the team explored causal associations in silico by bidirectional mediation analysis. The intestinal microbiome was analyzed at functional, taxonomic, and genetic levels.

The team used the eating disorder inventory-3 (EDI-3) questionnaire to assess eating behaviors and insulin resistance was assessed using the homoeostatic model assessment for insulin resistance (HOMA-IR) tool. The team examined covariations between bacterial abundance at species and genus levels and clinical variables for AN cases and controls. Linear regression modeling was performed, adjusting for confounders such as age, smoking status, medications, and body mass index (BMI).

Further, the team evaluated the growth dynamics of gut bacteria by calculating peak-to-trough ratios (PTR) using the metagenomic dataset. The functional modules of gut bacteria were identified using gut-brain modules (GBMs) and gut metabolic modules (GMMs). Differences in bacterial genomics were explored based on the Canberra distance of bacterial structural variant profiles.

​​​​​​​Graphical abstract of the study workflow and findings.

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Results

Several bacterial organisms (including Clostridium) were altered among individuals with anorexia nervosa and were associated with mental well-being and eating behavior estimates. Bacterial functional-type modules related to neurotransmitter degradation were enriched among those with anorexia nervosa. Further, several structural variants (SVs) in bacterial organisms were associated with the metabolic characteristics of anorexia nervosa.

The findings indicated a probable role of the intestinal microbiome in AN-associated changes concerning satiety and the metabolism of secondary bile acids. The metabolomic analysis indicated an elevation in metabolites linked to lowered food consumption (including taurine-hyodeoxycholic acid, taurine-α-muricholic acid, and indole-3-propionic acid molecules). Causal inference analysis indicated that serological bacterial metabolites probably mediate the effect of gut microbial alterations on anorexia nervosa. At the phylum level, AN microbiome samples showed lowered Actinobacteriota and Bacteroidota counts. Among families of bacteria, Christensenellaceae species, particularly CAG-138, showed the most significant enrichment in AN.

At the genus level, elevated Lactobacillus counts were observed in the AN microbiota. The Ruminococcacea-enterotype was more prevalent in cases of AN. Species-level analysis indicated greater β-diversity among AN-affected women. In AN, Roseburia inulinivorans and Roseburia intestinalis were depleted, whereas those of Erysipelatoclostridium ramosum, Blautia species CAG, and Enterocloster bolteae innocuum (Clostridium) were increased. Clostridium counts correlated positively with eating disorder scores. The abundance of Bifidobacterium and Parasutterella, in absolute terms, showed positive correlations with perfectionism and body dissatisfaction, respectively.

Absolute Brachyspira count showed a positive association with ‘drive for thinness’ markers in anorexia nervosa. Median values for PTR markedly differed between individuals with AN and controls. Women with AN were leaner, had lower fasting serological insulin, glucose, and C-reactive protein (CRP) levels, and were more sensitive to insulin than controls. Bacterial organisms with significant growth retardation, among AN case individuals included Alistipes finegoldii, Akkermansia muciniphila, Eubacterium siraeum, Coprococcus catus, SS3/4, and Odoribacter splanchnicus.

In addition, the intestinal virome was altered among AN-affected individuals, including lowered bacterial-viral interactions, due to attenuated interactions of viruses with short-chain fatty acid (SCFA)-producing bacteria, including Roseburia inulinivorans, Roseburia hominis, and Faecalibacterium prausnitzii. The team observed greater viral richness and Shannon diversity in the fecal samples of AN cases compared to controls. Notably, 25/30 viruses increased in AN were Lactococcus bacteriophages. The abundance of GBMs for serotonin synthesis and degradation of tryptophan, glutamate, and dopamine, were enriched in AN.

The team detected 2,423 and 5,056 variable SVs and deletion SVs, respectively, across 56 species of bacteria, including Bacteroides uniformis, Faecalibacterium prausnitzii, Parabacteroides distasonis, Methanobrevibacter smithii. Individuals with AN lacking the genomic region of B. uniformis had greater scores for self-denial and bulimia. The genetic deletion in B. uniformis could result in the deficiency of thiamine, a vitamin associated with intestinal and mental health. The serotonin synthesis module causally affected BMI through glycoursodeoxycholic acid, which is upregulated by serotonin.

Serum leucine mediated the influence of B. vulgatus counts on glucose homeostasis. Mice receiving AN individuals’ fecal transplants initially lost more weight with a slower gain of weight with time than those receiving fecal transplants of control individuals. The finding was related to greater levels of hypothalamic appetite-suppressing genes and thermogenesis-associated genes in the adipose tissues of mice receiving fecal transplants from individuals with AN.

Based on the study findings, gut microbial disruptions may contribute to the pathogenesis of AN.

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Study finds sugary beverages increase dementia risk, while natural juices may help prevent it

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In an article published in the journal Current Opinion in Microbiology, scientists have provided a detailed overview of the factors affecting maternal gut microbiota during pregnancy and its impact on maternal and infant health.

Study: Sugary beverages and genetic risk in relation to brain structure and incident dementia: a prospective cohort study. Image Credit: Africa Studio / ShutterstockStudy: Sugary beverages and genetic risk in relation to brain structure and incident dementia: a prospective cohort study. Image Credit: Africa Studio / Shutterstock

Background

Pregnancy is associated with a wide range of hormonal, immunological, and metabolic changes needed for fetal development. The most notable changes include increased cardiac output, higher levels of T regulatory cells, and alteration in gut microbiome composition.

Alteration in gut microbiota composition and diversity is associated with changes in women’s metabolic, immunological, and neurological processes, irrespective of pregnancy status. In addition, changes in gut microbiota composition are known to affect insulin sensitivity. In children with type 1 diabetes, functional and metabolic changes in gut microbiota have been documented.

Alteration in gut microbiota during pregnancy

Only limited evidence is available to thoroughly understand the changes in gut microbiota during pregnancy and its impact on maternal and fetal health. However, according to the available literature, low-grade inflammation at the intestinal mucosa as well as hormonal changes, might be responsible for gut microbiota alteration during pregnancy.

Regarding hormonal changes, pregnancy-related induction in progesterone levels is known to directly associate with increased Bifidobacterium levels in women. Bifidobacterium is a beneficial bacterium that naturally resides in the intestine. Therefore, the gut-to-gut transmission of this bacterium from the mother to the infant is crucial during the neonatal period. In infants, this bacterium helps degrade human milk oligosaccharides coming from maternal milk, in addition to developing infant gut microbiota and immune system.

Factors influencing maternal gut microbiota during pregnancy

Adult human gut microbiota can be influenced by many factors, including body mass index (BMI), medications, diseases, environment, and lifestyle (diet, physical activity, smoking, and drinking habits). Pre-pregnancy exposure to these factors can lead to structural and functional alteration in maternal gut microbiota during pregnancy.

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Animal studies have shown that maternal diet influences maternal and infant gut microbiota composition before and during pregnancy. Both pre-pregnancy body weight and pregnancy-related weight gain have been found to alter the composition and diversity of maternal gut microbiota.

Infant gut microbiota are influenced by the way they are delivered. For example, infants delivered vaginally have been shown to gain beneficial changes in gut microbiota compared to those delivered by c-section.

Functional studies in animals have shown that smoking-related nicotine exposure during pregnancy affects maternal gut microbiota, which in turn alters fetal exposure levels to circulating short-chain fatty acids and leptin during in-utero development.

Certain diseases before pregnancy, such as inflammatory bowel disease, have been found to influence maternal microbiota during pregnancy. The microbiota of the pregnant mother’s gut has also been shown to be affected pre-pregnancy and during pregnancy by certain medications, including antibiotics, proton-pump inhibitors, metformin, laxatives, and probiotics.

Maternal health impact of altered gut microbiota

Studies have found maternal gut microbiota alteration during pregnancy is associated with pregnancy complications, including gestational diabetes and preeclampsia.  

Gestational diabetes

A spontaneous induction in blood glucose levels during pregnancy is medically termed gestational diabetes. Studies have shown that a reduced abundance of beneficial bacteria and an increased abundance of pathogenic bacteria are responsible for the onset of gestational diabetes.

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In the microbiome of gestational diabetes patients, an increased abundance of membrane transport, energy metabolism, lipopolysaccharides, and phosphotransferase system pathways has been observed. Recent evidence indicates that gut microbiota-derived dopamine deficiency in the blood, impaired production of short-chain fatty acids, and excessive metabolic inflammation are collectively responsible for the development of gestational diabetes.

Preeclampsia

Preeclampsia is characterized by new-onset hypertension, proteinuria, and organ dysfunction during pregnancy. Studies involving pregnant women with preeclampsia have found gut microbiota dysbiosis (imbalance in gut microbiota composition) and increased plasma levels of lipopolysaccharide and trimethylamine N-oxide.

Recent evidence indicates that preeclampsia onset is associated with reduced bacterial diversity in gut microbiota. Specifically, the changes in gut microbiota include a depletion in beneficial bacteria and an enrichment in opportunistic bacteria.

Some mechanistic studies have pointed out that gut microbiota dysbiosis induces immune imbalance and intestinal barrier disruption in pregnant women, leading to the translocation of bacteria to the intrauterine cavity, placental inflammation, and poor placentation. All these factors collectively contribute to the development of preeclampsia.

Infant health impact of altered gut microbiota

Alteration in maternal gut microbiota has been found to affect the fetus’s neurodevelopment via signaling microbially modulated metabolites to neurons in the developing brain. These changes can have long-term effects on an infant’s behaviors.

Maternal microbiota-derived metabolites such as short-chain fatty acids are known to shape the metabolic system of infants. Some evidence has also indicated that maternal gut microbiota influences an infant’s susceptibility to allergic diseases.

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Journal reference:

Factors shaping maternal gut microbiome during pregnancy and the impact on infant health

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In an article published in the journal Current Opinion in Microbiology, scientists have provided a detailed overview of the factors affecting maternal gut microbiota during pregnancy and its impact on maternal and infant health.

Study: The maternal gut microbiome during pregnancy and its role in maternal and infant health. Image Credit: Design_Cells / ShutterstockStudy: The maternal gut microbiome during pregnancy and its role in maternal and infant health. Image Credit: Design_Cells / Shutterstock

Background

Pregnancy is associated with a wide range of hormonal, immunological, and metabolic changes needed for fetal development. The most notable changes include increased cardiac output, higher levels of T regulatory cells, and alteration in gut microbiome composition.

Alteration in gut microbiota composition and diversity is associated with changes in women’s metabolic, immunological, and neurological processes, irrespective of pregnancy status. In addition, changes in gut microbiota composition are known to affect insulin sensitivity. In children with type 1 diabetes, functional and metabolic changes in gut microbiota have been documented.

Alteration in gut microbiota during pregnancy

Only limited evidence is available to thoroughly understand the changes in gut microbiota during pregnancy and its impact on maternal and fetal health. However, according to the available literature, low-grade inflammation at the intestinal mucosa as well as hormonal changes, might be responsible for gut microbiota alteration during pregnancy.

Regarding hormonal changes, pregnancy-related induction in progesterone levels is known to directly associate with increased Bifidobacterium levels in women. Bifidobacterium is a beneficial bacterium that naturally resides in the intestine. Therefore, the gut-to-gut transmission of this bacterium from the mother to the infant is crucial during the neonatal period. In infants, this bacterium helps degrade human milk oligosaccharides coming from maternal milk, in addition to developing infant gut microbiota and immune system.

Factors influencing maternal gut microbiota during pregnancy

Adult human gut microbiota can be influenced by many factors, including body mass index (BMI), medications, diseases, environment, and lifestyle (diet, physical activity, smoking, and drinking habits). Pre-pregnancy exposure to these factors can lead to structural and functional alteration in maternal gut microbiota during pregnancy.

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Animal studies have shown that maternal diet influences maternal and infant gut microbiota composition before and during pregnancy. Both pre-pregnancy body weight and pregnancy-related weight gain have been found to alter the composition and diversity of maternal gut microbiota.

Mode of delivery has been found to influence infant gut microbiota. For example, infants delivered vaginally have been shown to gain beneficial changes in gut microbiota compared to those delivered by c-section.

Functional studies in animals have shown that smoking-related nicotine exposure during pregnancy affects maternal gut microbiota, which in turn alters fetal exposure levels to circulating short-chain fatty acids and leptin during in-utero development.

Certain diseases before pregnancy, such as inflammatory bowel disease, have been found to influence maternal microbiota during pregnancy. Similarly, pre-pregnancy and during-pregnancy consumption of certain medications, including antibiotics, proton-pump inhibitors, metformin, laxatives, and probiotics, has been found to influence maternal gut microbiota during pregnancy.

Maternal health impact of altered gut microbiota

Studies have found maternal gut microbiota alteration during pregnancy is associated with pregnancy complications, including gestational diabetes and preeclampsia.  

Gestational diabetes

A spontaneous induction in blood glucose levels during pregnancy is medically termed gestational diabetes. Studies have shown that a reduced abundance of beneficial bacteria and an increased abundance of pathogenic bacteria are responsible for the onset of gestational diabetes.

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In the microbiome of gestational diabetes patients, an increased abundance of membrane transport, energy metabolism, lipopolysaccharides, and phosphotransferase system pathways has been observed. Recent evidence indicates that gut microbiota-derived dopamine deficiency in the blood, impaired production of short-chain fatty acids, and excessive metabolic inflammation are collectively responsible for the development of gestational diabetes.

Preeclampsia

Preeclampsia is characterized by new-onset hypertension, proteinuria, and organ dysfunction during pregnancy. Studies involving pregnant women with preeclampsia have found gut microbiota dysbiosis (imbalance in gut microbiota composition) and increased plasma levels of lipopolysaccharide and trimethylamine N-oxide.

Recent evidence indicates that preeclampsia onset is associated with reduced bacterial diversity in gut microbiota. Specifically, the changes in gut microbiota include a depletion in beneficial bacteria and an enrichment in opportunistic bacteria.

Some mechanistic studies have pointed out that gut microbiota dysbiosis induces immune imbalance and intestinal barrier disruption in pregnant women, leading to the translocation of bacteria to the intrauterine cavity, placental inflammation, and poor placentation. All these factors collectively contribute to the development of preeclampsia.

Infant health impact of altered gut microbiota

Alteration in maternal gut microbiota has been found to affect the fetus’s neurodevelopment via signaling microbially modulated metabolites to neurons in the developing brain. These changes can have long-term effects on an infant’s behaviors.

Maternal microbiota-derived metabolites such as short-chain fatty acids are known to shape the metabolic system of infants. Some evidence has also indicated that maternal gut microbiota influences an infant’s susceptibility to allergic diseases.

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Journal reference:

The gut microbiome in anorexia nervosa

Hildebrandt, T., Peyser, D. The gut microbiome in anorexia nervosa.
Nat Microbiol (2023). https://doi.org/10.1038/s41564-023-01372-4

Review on factors related to variations in human microbiota

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:

Gut-on-a-chip devices can bridge lab models and human biology

The gut is one of the most complex organs in the body. Inside, it teems with a diverse microbial population that interacts and cooperates with intestinal cells to digest food and drugs. Disruptions in this microbiome have strong links to a wide spectrum of diseases, such as inflammatory bowel disease, obesity, asthma, and even psychological and behavioral disorders.

Valid models of the gut are therefore immensely useful for understanding its function and associated ailments. In APL Bioengineering, by AIP Publishing, researchers from the University of California, Berkeley and Lawrence Berkeley National Lab described how gut-on-a-chip devices can bridge lab models and human biology.

Organ-on-a-chip devices are miniaturized models of human organs. They contain tiny microchannels where cells and tissue cultures interact with precisely controlled nutrients. Regulating the cell’s environment in such a way is crucial for creating realistic models of tissue.

Using these models avoids the time-consuming and costly challenges of clinical trials and the ethical issues behind animal testing.

“Medical research is currently facing major hurdles, both in terms of understanding the basic science governing the function of human organs and the research and development of new drugs and therapeutics,” said author Amin Valiei. “Access to valid models of human organs that can be studied conveniently in the lab can significantly accelerate scientific discoveries and the development of new medications.”

Modeling the microbiome is particularly difficult because of its unique environmental conditions. Through creative design, gut-on-a-chip devices can simulate many of these properties, such as the gut’s anaerobic atmosphere, fluid flow, and pulses of contraction/relaxation. Growing intestinal cells in this environment means that they more closely resemble human biology compared to standard laboratory cell cultures.

“Recent gut-on-a-chip models have demonstrated success in maintaining a viable coculture of the human intestinal cells and the microbiome for a few days and even up to weeks,” said Valiei. “This opens new ways to analyze the microbiome under biologically relevant conditions.”

The authors highlight key gut-on-a-chip devices and their success in simulating microbial and human cellular biology. They also describe current disease models and drug studies using the technology.

“Its unique capabilities make the organ-on-a-chip apt for plenty of research investigations in the future,” said Valiei.

The team is currently investigating dysbiosis, an imbalance in the gut microbial community with major health consequences. They aim to find innovative ways to diagnose, mitigate, and treat this condition.

Differences in gut microbiome diversity attributed to dietary patterns in children with obesity

In a recent study published in Microbiology Spectrum, researchers found that differences in the dietary patterns of children with normal weight and those who were overweight or obese contributed to variations in the gut microbiome diversity, virulence factors of gut bacteria, and metabolic function.

Study: Virulence factors of the gut microbiome are associated with BMI and metabolic blood parameters in children with obesity. Image Credit: Africa Studio / Shutterstock.com

Study: Virulence factors of the gut microbiome are associated with BMI and metabolic blood parameters in children with obesity. Image Credit: Africa Studio / Shutterstock.com

Background

A growing body of evidence indicates that gut microbiota has a significant role in various aspects of host metabolism, including digestion, harvesting of energy, and induction of low-grade inflammation. In addition, the genetic factors of the host, as well as other characteristics such as age, diet, immunity, and gender, influence the gut microbiome composition.

Research shows that bacterial diversity in the gut and the individual’s functional capacity vary between those with normal weight and obese individuals. Gut microbiome profile variations have also been linked to metabolic disorders, lipid accumulation, and inflammation.

Lipogenesis in the liver and the regulation of appetite through hormones are also associated with gut microbiome genes.

Aside from its role in adipogenesis, superoxide reduction, and the metabolism of vitamins, gut microbiota also regulates innate immunity and the systemic, low-grade inflammatory state that can contribute to fat deposition and obesity. Therefore, Dysbiosis, which is the imbalance of gut microbiota, combined with diet, likely has a significant role in the development of obesity.

About the study

In the present study, researchers conducted a cross-sectional analysis of data from 45 children between the ages of six and 12 to determine the association between gut microbiota and obesity.

Questionnaires were used to obtain information on dietary frequencies, gender, age, and body mass index (BMI). Based on the World Health Organization (WHO) z-scores, in which BMI is adjusted for gender and age, the children were classified into two categories of overweight and obese (OWOB) and normal weight (NW).

Data from food frequency questionnaires were used to classify the dietary habits of children into two nutritional patterns. To this end, Pattern 1 was characterized by complex carbohydrates and proteins, whereas Pattern 2 comprised simple carbohydrates and saturated fats.

Shotgun metagenomics was used to assess the taxonomic diversity of the gut microbiota and metabolic capacity from genomic deoxyribonucleic acid (DNA) extracted from fecal samples. Clade-specific markers were used for the taxonomic and functional assessment of the gut bacteria. Additionally, reverse Simpson and Shannon diversity indices were calculated.

The virulence factor database was used to screen for virulence factor genes, whereas multivariate linear modeling was used to determine the association between the taxa, virulence factors, and function of gut microbes and covariates of diet, serology, and anthropometric measurements.

Study findings

Significant differences between the alpha and beta diversity of the gut microbiota were observed between the children in the NW and OWOB groups, thus suggesting that specific phyla of bacteria contribute to higher levels of energy harvest.

Furthermore, species such as Ruminococcus species, Victivallis vadensis, Mitsuokella multacida, Alistipes species, Clostridium species, and Acinetobacter johnsonii were linked to healthier metabolic parameters.

In contrast, an increase in the abundance of bacteria such as Veillonellaceae, Lactococcus, Fusicatenibacter saccharivorans, Fusicatenibacter prausnitzii, Eubacterium, Roseburia, Dialister, Coprococcus catus, Bifidobacterium, and Bilophila was identified in children with pro-inflammatory conditions and obesity.

Bacteria such as Citrobacter europaeus, Citrobacter youngae, Klebsiella variicola, Enterococcus mundtii, Gemella morbillorum, and Citrobacter portucalensis were associated with higher lipid and sugar intake, as well as higher blood biochemistry values and anthropometric measurements.

Diets high in fats and simple carbohydrates have been associated with the abundance of Citrobacter and Klebsiella species in the gut. Moreover, previous studies have indicated that these bacterial species are potential markers of inflammation, obesity, and an increase in fasting glucose.

The metabolism of menaquinones and gamma-glutamyl was negatively associated with BMI. Furthermore, the microbiomes of children in the NW group preserved a more consistent alpha diversity of virulence factors, while OWOB microbiomes exhibited a dominance of virulence factors.

Differences in the metabolic capacities pertaining to biosynthesis pathways of vitamins, carriers, amino acids, nucleotides, nucleosides, amines, and polyamines, as well as the degradation of nucleotides, nucleosides, and carbohydrate-sugars, were also found between the NW and OWOB groups.

Conclusions

Dietary profiles and the diversity of gut microbiota were found to be interconnected and associated with changes in metabolic parameters, the dominance of virulence factors, and obesity. Changes in gut microbiome diversity and relative abundance have been linked to obesity, inflammatory responses, and metabolic disorders.

Taken together, the study findings suggested that the prevalence of virulence factors, as well as the metabolic and genetic roles of gut microbiota in increasing inflammation, can help identify individuals at an increased risk of childhood obesity.

Journal reference:
  • Murga-Garrido, S. M., Ulloa-Pérez, E. J., Díaz-Benítez, C. E., et al. (2023). Virulence factors of the gut microbiome are associated with BMI and metabolic blood parameters in children with obesity. Microbiology Spectrum. doi:10.1128/spectrum.03382-22

What are the major findings of long COVID research?

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: