18 research outputs found

    Context-dependent costs and benefits of tuberculosis resistance traits in a wild mammalian host

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    Disease acts as a powerful driver of evolution in natural host populations, yet individuals in a population often vary in their susceptibility to infection. Energetic trade-offs between immune and reproductive investment lead to the evolution of distinct life history strategies, driven by the relative fitness costs and benefits of resisting infection. However, examples quantifying the cost of resistance outside of the laboratory are rare. Here, we observe two distinct forms of resistance to bovine tuberculosis (bTB), an important zoonotic pathogen, in a free-ranging African buffalo (Syncerus caffer) population. We characterize these phenotypes as “infection resistance,” in which hosts delay or prevent infection, and “proliferation resistance,” in which the host limits the spread of lesions caused by the pathogen after infection has occurred. We found weak evidence that infection resistance to bTB may be heritable in this buffalo population (h2 = 0.10) and comes at the cost of reduced body condition and marginally reduced survival once infected, but also associates with an overall higher reproductive rate. Infection-resistant animals thus appear to follow a “fast” pace-of-life syndrome, in that they reproduce more quickly but die upon infection. In contrast, proliferation resistance had no apparent costs and was associated with measures of positive host health—such as having a higher body condition and reproductive rate. This study quantifies striking phenotypic variation in pathogen resistance and provides evidence for a link between life history variation and a disease resistance trait in a wild mammalian host population

    Framing the discussion of microorganisms as a facet of social equity in human health

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    What do “microbes” have to do with social equity? These microorganisms are integral to our health, that of our natural environment, and even the “health” of the environments we build. The loss, gain, and retention of microorganisms—their flow between humans and the environment—can greatly impact our health. It is well-known that inequalities in access to perinatal care, healthy foods, quality housing, and the natural environment can create and arise from social inequality. Here, we focus on the argument that access to beneficial microorganisms is a facet of public health, and health inequality may be compounded by inequitable microbial exposure

    History of breastfeeding but not mode of delivery shapes the gut microbiome in childhood.

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    BackgroundThe naĂŻve neonatal gut is sensitive to early life experiences. Events during this critical developmental window may have life-long impacts on the gut microbiota. Two experiences that have been associated with variation in the gut microbiome in infancy are mode of delivery and feeding practices (eg, breastfeeding). It remains unclear whether these early experiences are responsible for microbial differences beyond toddlerhood.AimsOur study examined whether mode of delivery and infant feeding practices are associated with differences in the child and adolescent microbiome.Design, subjects, measuresWe used an adoption-sibling design to compare genetically related siblings who were reared together or apart. Gut microbiome samples were collected from 73 children (M = 11 years, SD = 3 years, range = 3-18 years). Parents reported on child breastfeeding history, age, sex, height, and weight. Mode of delivery was collected through medical records and phone interviews.ResultsNegative binomial mixed effects models were used to identify whether mode of delivery and feeding practices were related to differences in phylum and genus-level abundance of bacteria found in the gut of child participants. Covariates included age, sex, and body mass index. Genetic relatedness and rearing environment were accounted for as random effects. We observed a significant association between lack of breastfeeding during infancy and a greater number of the genus Bacteroides in stool in childhood and adolescence.ConclusionThe absence of breastfeeding may impart lasting effects on the gut microbiome well into childhood

    Host genomic variation shapes gut microbiome diversity in threespine stickleback fish

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    ABSTRACT Variation among host-associated microbiomes is well documented across species, populations, and individuals. While numerous factors can contribute to this variation, understanding the influence of host genetic differences on microbial variation is particularly important for predicting co-evolutionary dynamics between hosts and their microbiota. Functional understanding of host genetic and microbial covariation is also of biomedical relevance, for example, providing insights into why some humans are more susceptible to chronic disorders like inflammatory bowel diseases. Unfortunately, disentangling the relative contribution to microbiome variation of host genetics from the environment has been difficult, particularly in humans where confounding environmental effects cannot be completely controlled experimentally. While isogenic laboratory models can be used in controlled environments, the effects on microbiomes of induced large-effect mutations may not recapitulate those of genetic variation observed in nature. Few studies have tested for the direct influence of natural host genetic variation on microbiome differences within a highly controlled environment in which hosts interact freely. To fill this gap, we performed a common garden experiment using families of genetically divergent populations of threespine stickleback fish—an outbred model organism commonly used for determining the genetic basis of complex traits in the context of natural genetic variation. Using germ-free derivation of divergent lines and hybrids between them in this experimental framework, we detected a clear, positive association between stickleback genetic dissimilarity and microbiome dissimilarity. With RAD-seq data, we identified regions of the genome that contributed most significantly to this relationship, providing insight into the genomic architecture of gut microbiome variation. IMPORTANCE A major focus of host-microbe research is to understand how genetic differences, of various magnitudes, among hosts translate to differences in their microbiomes. This has been challenging for animal hosts, including humans, because it is difficult to control environmental variables tightly enough to isolate direct genetic effects on the microbiome. Our work in stickleback fish is a significant contribution because our experimental approach allowed strict control over environmental factors, including standardization of the microbiome from the earliest stage of development and unrestricted co-housing of fish in a truly common environment. Furthermore, we measured host genetic variation over 2,000 regions of the stickleback genome, comparing this information and microbiome composition data among fish from very similar and very different genetic backgrounds. Our findings highlight how differences in the host genome influence microbiome diversity and make a case for future manipulative microbiome experiments that use host systems with naturally occurring genetic variation

    Using a sibling-adoption design to parse genetic and environmental influences on children's body mass index (BMI).

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    Dietary and physical activity behaviors formed early in life can increase risk for childhood obesity and have continued negative consequences for lifelong health. Previous research has highlighted the importance of both genetic and environmental (e.g., cultural environment or parental lifestyle) contributions to obesity risk, although these studies typically involve genetically-related individuals residing in the same household, where genetic similarity and rearing environment are inextricably linked. Here we utilize a sibling-adoption design to independently estimate genetic and environmental contributions to obesity risk in childhood and describe how these influences might vary as children age. As part of a prospective adoption study, the current investigation used data from biological siblings reared either apart or together, and nonbiological siblings reared together to estimate the contributions of genetics and environment to body mass indices (BMI) in a large cohort of children (N = 711). We used a variance partitioning model to allocate variation in BMI to that which is due to shared genetics, common environment, or unique environment in this cohort during middle childhood and adolescence. We found 63% of the total variance in BMI could be attributed to heritable factors in middle childhood sibling pairs (age 5-11.99; 95% CI [0.41,0.85]). Additionally, we observed that common environment explained 31% of variation in BMI in this group (95% CI [0.11,0.5]), with unique environment and error explaining the remaining variance. We failed to detect an influence of genetics or common environment in older sibling pairs (12-18) or pairs spanning childhood and adolescence (large sibling age difference), but home type (adoptive versus birth) was an important predictor of BMI in adolescence. The presence of strong common environment effects during childhood suggests that early interventions at the family level in middle childhood could be effective in mitigating obesity risk in later childhood and adolescence

    Data from: Context-dependent costs and benefits of tuberculosis resistance traits in a wild mammalian host

    No full text
    Disease acts as a powerful driver of evolution in natural host populations, yet individuals in a population often vary in their susceptibility to infection. Energetic trade-offs between immune and reproductive investment lead to the evolution of distinct life-history strategies, driven by the relative fitness costs and benefits of resisting infection. However, examples quantifying the cost of resistance outside of the laboratory are rare. Here, we observe two distinct forms of resistance to bovine tuberculosis (bTB), an important zoonotic pathogen, in a free-ranging African buffalo (Syncerus caffer) population. We characterize these phenotypes as ‘infection resistance’, in which hosts delay or prevent infection, and ‘proliferation resistance’, in which the host limits the spread of lesions caused by the pathogen after infection has occurred. We found weak evidence that infection resistance to bTB may be heritable in this buffalo population (h2=0.10) and comes at the cost of reduced body condition and marginally reduced survival once infected, but also associates with an overall higher reproductive rate. Infection resistant animals thus appear to follow a ‘fast’ pace of life syndrome, in that they reproduce more quickly but die upon infection. In contrast, proliferation resistance had no apparent costs and was associated with measures of positive host health- such as having a higher body condition and reproductive rate. This study quantifies striking phenotypic variation in pathogen resistance and provides evidence for a link between life history variation and a disease resistance trait in a wild mammalian host population

    Genome-Wide Scan and Test of Candidate Genes in the Snail <i>Biomphalaria glabrata</i> Reveal New Locus Influencing Resistance to <i>Schistosoma mansoni</i>

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    <div><p>Background</p><p>New strategies to combat the global scourge of schistosomiasis may be revealed by increased understanding of the mechanisms by which the obligate snail host can resist the schistosome parasite. However, few molecular markers linked to resistance have been identified and characterized in snails.</p><p>Methodology/Principal Findings</p><p>Here we test six independent genetic loci for their influence on resistance to <i>Schistosoma mansoni</i> strain PR1 in the 13-16-R1 strain of the snail <i>Biomphalaria glabrata</i>. We first identify a genomic region, <i>RADres</i>, showing the highest differentiation between susceptible and resistant inbred lines among 1611 informative restriction-site associated DNA (RAD) markers, and show that it significantly influences resistance in an independent set of 439 outbred snails. The additive effect of each <i>RADres</i> resistance allele is 2-fold, similar to that of the previously identified resistance gene <i>sod1</i>. The data fit a model in which both loci contribute independently and additively to resistance, such that the odds of infection in homozygotes for the resistance alleles at both loci (13% infected) is 16-fold lower than the odds of infection in snails without any resistance alleles (70% infected). Genome-wide linkage disequilibrium is high, with both <i>sod1</i> and <i>RADres</i> residing on haplotype blocks >2Mb, and with other markers in each block also showing significant effects on resistance; thus the causal genes within these blocks remain to be demonstrated. Other candidate loci had no effect on resistance, including the Guadeloupe Resistance Complex and three genes (<i>aif</i>, <i>infPhox</i>, and <i>prx1)</i> with immunological roles and expression patterns tied to resistance, which must therefore be trans-regulated.</p><p>Conclusions/Significance</p><p>The loci <i>RADres</i> and <i>sod1</i> both have strong effects on resistance to <i>S</i>. <i>mansoni</i>. Future approaches to control schistosomiasis may benefit from further efforts to characterize and harness this natural genetic variation.</p></div

    Framing the discussion of microorganisms as a facet of social equity in human health.

    No full text
    What do "microbes" have to do with social equity? These microorganisms are integral to our health, that of our natural environment, and even the "health" of the environments we build. The loss, gain, and retention of microorganisms-their flow between humans and the environment-can greatly impact our health. It is well-known that inequalities in access to perinatal care, healthy foods, quality housing, and the natural environment can create and arise from social inequality. Here, we focus on the argument that access to beneficial microorganisms is a facet of public health, and health inequality may be compounded by inequitable microbial exposure

    Distribution of allele frequencies among RAD sites.

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    <p>We characterized 1611 informative RAD sites in 19 inbred lines by minor allele count (“MAC”) (maximum of 19; i.e. 50% allele frequency) and difference in MAC between susceptible (N = 10) and resistant (N = 9) lines (“MAC difference”, theoretical maximum = 18; i.e. 9 resistant lines fixed for one allele, 10 susceptible lines fixed for another). Circle sizes are proportional to the number of RAD sites showing each pattern. The cumulative percentage of RAD sites, starting with the highest observed MAC difference, is shown on the righthand y-axis. The highest MAC difference was observed for 10 RAD sites in perfect mutual LD, with a MAC of 13 and a MAC difference of 13, which we defined as the <i>RADres</i> region and examined further (red arrow; encompasses scaffolds of subsequently examined markers <i>RADres1</i> and <i>RADres2</i>). The one remaining RAD site with an equivalent MAC difference was also in high, but not perfect, LD with <i>RADres</i> (pink arrow; scaffold not examined further). The <i>sod1</i> haplotype block had a MAC difference of 5, which was higher than average but not an outlier (blue arrow).</p
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