Glycan-Based Shaping Of The Microbiota During Primate Evolution

AbstractGenes encoding certain glycosyltransferases are thought to be under relatively high selection pressure, due to the involvement of the glycans that they synthesize in host-microbe interactions. Here we used a mouse model to investigate whether the loss of α-1,3-galactosyltransferase (GGTA1) function and Galα1-3Galβ1-4GlcNAcβ1-R (αGal) expression during primate evolution might have affected host-microbiota interactions. We found that Ggta1 deletion in mice shaped the composition of the gut microbiota in relation to the bacterial species present. This occurred via an immunoglobulin (Ig)-dependent mechanism, associated with IgA targeting of αGal-expressing bacteria. Systemic infection by the Ig-shaped microbiota elicited a less severe form of sepsis than infection with the non-Ig-shaped microbiota. This suggests that in the absence of host αGal, the microbiota is shaped towards lower pathogenicity, likely providing a fitness gain to the host. We infer that high selection pressure exerted by bacterial sepsis may have contributed to increase frequency of GGTA1 loss-of-function mutations in ancestral primates that gave rise to humans.

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Glycan-based shaping of the microbiota during primate evolution

eLife ◽

10.7554/elife.67450 ◽

2021 ◽

Vol 10 ◽

Author(s):

Sumnima Singh ◽

Patricia Bastos-Amador ◽

Jessica Ann Thompson ◽

Mauro Truglio ◽

Bahtiyar Yilmaz ◽

...

Keyword(s):

Systemic Infection ◽

Primate Evolution ◽

Severe Form ◽

Loss Of Function ◽

Bacterial Sepsis ◽

Genes Encoding ◽

Microbe Interactions ◽

Host Microbe Interactions ◽

High Selection ◽

Dependent Mechanism

Genes encoding glycosyltransferases can be under relatively high selection pressure, likely due to the involvement of the glycans synthesized in host-microbe interactions. Here, we used mice as an experimental model system to investigate whether loss of α−1,3-galactosyltransferase gene (GGTA1) function and Galα1-3Galβ1-4GlcNAcβ1-R (αGal) glycan expression affects host-microbiota interactions, as might have occurred during primate evolution. We found that Ggta1 deletion shaped the composition of the gut microbiota. This occurred via an immunoglobulin (Ig)-dependent mechanism, associated with targeting of αGal-expressing bacteria by IgA. Systemic infection with an Ig-shaped microbiota inoculum elicited a less severe form of sepsis compared to infection with non-Ig-shaped microbiota. This suggests that in the absence of host αGal, antibodies can shape the microbiota towards lower pathogenicity. Given the fitness cost imposed by bacterial sepsis, we infer that the observed reduction in microbiota pathogenicity upon Ggta1 deletion in mice may have contributed to increase the frequency of GGTA1 loss-of-function mutations in ancestral primates that gave rise to humans.

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Understanding the host-microbe interactions using metabolic modeling

Microbiome ◽

10.1186/s40168-020-00955-1 ◽

2021 ◽

Vol 9 (1) ◽

Author(s):

Jack Jansma ◽

Sahar El Aidy

Keyword(s):

Human Health ◽

Flux Balance Analysis ◽

Bacterial Species ◽

Flux Balance ◽

Interaction Field ◽

In Silico Simulation ◽

Balance Analysis ◽

Microbe Interactions ◽

Host Microbe Interactions ◽

Genome Scale

AbstractThe human gut harbors an enormous number of symbiotic microbes, which is vital for human health. However, interactions within the complex microbiota community and between the microbiota and its host are challenging to elucidate, limiting development in the treatment for a variety of diseases associated with microbiota dysbiosis. Using in silico simulation methods based on flux balance analysis, those interactions can be better investigated. Flux balance analysis uses an annotated genome-scale reconstruction of a metabolic network to determine the distribution of metabolic fluxes that represent the complete metabolism of a bacterium in a certain metabolic environment such as the gut. Simulation of a set of bacterial species in a shared metabolic environment can enable the study of the effect of numerous perturbations, such as dietary changes or addition of a probiotic species in a personalized manner. This review aims to introduce to experimental biologists the possible applications of flux balance analysis in the host-microbiota interaction field and discusses its potential use to improve human health.

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249 Influence of filaggrin loss-of-function mutations in host–microbe interactions during atopic skin inflammation

Journal of Investigative Dermatology ◽

10.1016/j.jid.2019.07.250 ◽

2019 ◽

Vol 139 (9) ◽

pp. S257

Author(s):

P. Olah ◽

E. Szlávicz ◽

E. Consortium ◽

E. Rodriguez ◽

S. Weidinger ◽

...

Keyword(s):

Skin Inflammation ◽

Loss Of Function ◽

Atopic Skin ◽

Microbe Interactions ◽

Host Microbe Interactions

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Expression of heat shock proteins 27 and 72 correlates with specific commensal microbes in different regions of porcine gastrointestinal tract

AJP Gastrointestinal and Liver Physiology ◽

10.1152/ajpgi.00299.2013 ◽

2014 ◽

Vol 306 (12) ◽

pp. G1033-G1041 ◽

Cited By ~ 17

Author(s):

Hao-Yu Liu ◽

Johan Dicksved ◽

Torbjörn Lundh ◽

Jan Erik Lindberg

Keyword(s):

Immune System ◽

Heat Shock ◽

Heat Shock Proteins ◽

Bacterial Species ◽

Host Immune System ◽

Gi Tract ◽

Microbe Interactions ◽

Cell Type Specific ◽

Host Microbe Interactions ◽

Shock Proteins

The gastrointestinal (GI) tract of mammals is inhabited by trillions of microorganisms, resulting in exceedingly complex networking. The interaction between distinct bacterial species and the host immune system is essential in maintaining homeostasis in the gut ecosystem. For instance, the gut commensal microbiota dictates intestinal mucosa maturation and its abundant immune components, such as cytoprotective heat shock proteins (HSP). Here we examined physiological expression of HSP in the normal porcine GI tract and found it to be gut region- and cell type-specific in response to dietary components, microbes, and microbial metabolites to which the mucosa surface is exposed. Correlations between HSP72 expression and ileal Lactobacillus spp. and colonic clostridia species, and between HSP27 expression and uronic acid ingestion, were important interplays identified here. Thus this study provides novel insights into host-microbe interactions shaping the immune system that are modifiable by dietary regime.

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Refined quantification of infection bottlenecks and pathogen dissemination with STAMPR

10.1101/2021.04.28.441820 ◽

2021 ◽

Author(s):

Karthik Hullahalli ◽

Justin R. Pritchard ◽

Matthew K. Waldor

Keyword(s):

Population Dynamics ◽

Allelic Diversity ◽

Systemic Infection ◽

Pathogen Population ◽

Founding Population ◽

Population Sizes ◽

Microbe Interactions ◽

Microbial Population Dynamics ◽

Host Microbe Interactions ◽

Using Data

AbstractPathogen population dynamics during infection are critical determinants of infection susceptibility and define patterns of dissemination. However, deciphering pathogen population dynamics, particularly founding population sizes in host organs and patterns of dissemination between organs, is difficult due to the fact that measuring bacterial burden alone is insufficient to observe these patterns. Introduction of allelic diversity into otherwise identical bacteria using DNA barcodes enables sequencing-based measurements of these parameters, in a method known as STAMP (Sequence Tag-Based analysis of Microbial Population dynamics). However, bacteria often undergo unequal expansion within host organs, resulting in marked differences in the frequencies of barcodes in input and output libraries. Here, we show that these differences confound STAMP-based analyses of founding population sizes and dissemination patterns. We present STAMPR, a successor to STAMP that accounts for such population expansions. Using data from systemic infection of barcoded Extraintestinal Pathogenic E. coli we show that this new framework along with the metrics it yields enhances the fidelity of measurements of bottlenecks and dissemination patterns. STAMPR was also validated on an independent, barcoded Pseudomonas aeruginosa dataset, uncovering new patterns of dissemination within the data. This framework (available at https://github.com/hullahalli/stampr_rtisan), when coupled with barcoded datasets, enables a more complete assessment of within-host bacterial population dynamics.ImportanceBarcoded bacteria are often employed to monitor pathogen population dynamics during infection. The accuracy of these measurements is diminished by unequal bacterial expansion rates. Here, we develop computational tools to circumvent this limitation and establish additional metrics that collectively enhance the fidelity of measuring within-host pathogen founding population sizes and dissemination patterns. These new tools will benefit future studies of the dynamics of pathogens and symbionts within their respective hosts, and may have additional barcode-based applications beyond host-microbe interactions.

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Streptococcal pyogenic exotoxin B (SpeB) boosts the contact system via binding of α-1 antitrypsin

Biochemical Journal ◽

10.1042/bj20100984 ◽

2011 ◽

Vol 434 (1) ◽

pp. 123-132 ◽

Cited By ~ 7

Author(s):

Louise Meinert Niclasen ◽

Johan G. Olsen ◽

Robert Dagil ◽

Zhang Qing ◽

Ole E. Sørensen ◽

...

Keyword(s):

Bacterial Infections ◽

Systemic Infection ◽

Contact System ◽

Bacterial Survival ◽

Bacterial Killing ◽

Additional Layer ◽

Streptococcal Pyrogenic Exotoxin B ◽

Microbe Interactions ◽

System Activation ◽

Host Microbe Interactions

The Streptococcus pyogenes cysteine protease SpeB (streptococcal pyrogenic exotoxin B) is important for the invasive potential of the bacteria, but its production is down-regulated following systemic infection. This prompted us to investigate if SpeB potentiated the host immune response after systemic spreading. Addition of SpeB to human plasma increased plasma-mediated bacterial killing and prolonged coagulation time through the intrinsic pathway of coagulation. This effect was independent of the enzymatic activity of SpeB and was mediated by a non-covalent medium-affinity binding and modification of the serpin A1AT (α-1 antitrypsin). Consequently, addition of A1AT to plasma increased bacterial survival. Sequestration of A1AT by SpeB led to enhanced contact system activation, supported by increased bacterial growth in prekallikrein deficient plasma. In a mouse model of systemic infection, administration of SpeB reduced significantly bacterial dissemination. The findings reveal an additional layer of complexity to host–microbe interactions that may be of benefit in the treatment of severe bacterial infections.

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Genome Sequence of Elizabethkingia anophelis Strain EaAs1, Isolated from the Asian Malaria Mosquito Anopheles stephensi

Genome Announcements ◽

10.1128/genomea.00084-16 ◽

2016 ◽

Vol 4 (2) ◽

Cited By ~ 12

Author(s):

Juan Antonio Raygoza Garay ◽

Grant L. Hughes ◽

Vikas Koundal ◽

Jason L. Rasgon ◽

Michael M. Mwangi

Keyword(s):

Genome Sequence ◽

Anopheles Stephensi ◽

Bacterial Species ◽

Malaria Mosquito ◽

Gram Negative ◽

Microbe Interactions ◽

Host Microbe Interactions

We sequenced the genome of a strain of the Gram-negative bacterial species Elizabethkingia anophelis , which is an important component of the Anopheles mosquito microbiome. This genome sequence will add to the list of resources used to examine host-microbe interactions in mosquitoes.

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Understanding the host-microbe interactions using metabolic modeling

10.1101/2020.06.12.147918 ◽

2020 ◽

Author(s):

Jack Jansma ◽

Sahar El Aidy

Keyword(s):

Human Health ◽

Flux Balance Analysis ◽

Bacterial Species ◽

Flux Balance ◽

Balance Analysis ◽

Microbe Interactions ◽

Host Microbe Interactions ◽

Genome Scale ◽

Enormous Number ◽

Potential Use

AbstractThe human gut harbors an enormous number of symbiotic microbes, which is vital for human health. However, interactions within the complex microbiota community and between the microbiota and its host are challenging to elucidate, limiting development in the treatment for a variety of diseases associated with microbiota dysbiosis. Using In silico simulation methods based on flux balance analysis, those interactions can be better investigated. Flux balance analysis uses an annotated genome-scale reconstruction of a metabolic network to determine the distribution of metabolic fluxes that represent the complete metabolism of a bacterium in a certain metabolic environment such as the gut. Simulation of a set of bacterial species in a shared metabolic environment can enable the study of the effect of numerous perturbations, such as dietary changes or addition of a probiotic species in a personalized manner. This review aims to introduce these applications of flux balance analysis to experimental biologists and discusses its potential use to improve human health.

Download Full-text