Current Genomics - Volume 19, Issue 8, 2018

Epigenetic processes during early brain development can function as ‘developmental switches’ that contribute to the stability of long-term effects of early environmental influences by programming central feedback mechanisms of the HPA axis and other neural networks. In this thematic review, we summarize accumulated evidence for a dual-activation of stress-related and sensory networks underlying the epigenetic programming effects of early life stress. We discuss findings indicating epigenetic programming of stress-related genes with impact on HPA axis function, the interaction of epigenetic mechanisms with neural activity in stress-related neural networks, epigenetic effects of glucocorticoid exposure, and the impact of stress on sensory development. Based on these findings, we propose that the combined activation of stress-related neural networks and stressor-specific sensory networks leads to both neural and hormonal priming of the epigenetic machinery, which sensitizes these networks for developmental programming effects. This allows stressor-specific adaptations later in life, but may also lead to functional mal-adaptations, depending on timing and intensity of the stressor. Finally, we discuss methodological and clinical implications of the dual-activation hypothesis. We emphasize that, in addition to modifications in stress-related networks, we need to account for functional modifications in sensory networks and their epigenetic underpinnings to elucidate the longterm effects of early life stress.

Early life adversity is associated with both persistent disruptions in the hypothalamicpituitary- adrenal (HPA) axis and psychiatric symptoms. Glucocorticoid receptors (GRs), which are encoded by the NR3C1 gene, bind to cortisol and other glucocorticoids to create a negative feedback loop within the HPA axis to regulate the body's neuroendocrine response to stress. Excess methylation of a promoter sequence within NR3C1 that attenuates GR expression, however, has been associated with both early life adversity and psychopathology. As critical regulators within the HPA axis, GRs and their epigenetic regulation may mediate the link between early life adversity and the onset of psychopathology. The present review discusses this work as one mechanism by which stress may get under the skin to disrupt HPA functioning at an epigenetic level and create long-lasting vulnerabilities in the stress regulatory system that subsequently predispose individuals to psychopathology. Spanning prenatal influences to critical periods of early life and adolescence, we detail the impact that early adversity has on GR expression, physiological responses to stress, and their implications for long-term stress management. We next propose a dual transmission hypothesis regarding both genomic and nongenomic mechanisms by which chronic and acute stress propagate through numerous generations. Lastly, we outline several directions for future research, including potential reversibility of methylation patterns and its functional implications, variation in behavior determined solely by NR3C1, and consensus on which specific promoter regions should be studied.

Early life stress in humans (i.e. maltreatment, violence exposure, loss of a loved one) and in rodents (i.e. disrupted attachment or nesting, electric shock, restraint, predator odor) occurs during critical steps of neural circuit formation. ELS in humans is associated with increased risk for developmental psychopathology, including anxious and depressive phenotypes. The biological mechanisms underlying these potentially persistent maladaptive changes involve long-term epigenetic modifications, which have been suggested to be potentially transmissible to subsequent generations. DNA methylation is an epigenetic mechanism that modifies gene expression patterns in response to environmental challenges and influences mutation rates. It remains to be seen whether a functionally relevant fraction of DNA methylation marks can escape genome-wide erasures that occur in primordial germ cells and after fertilization within the zygote. Early life-stress-triggered changes in epigenetic mediated transmission of acquired behavioral traits among humans have been assessed mainly by targeting genes involved in the hypothalamic-pituitary-adrenal (HPA) axis, such as NR3C1 and FKBP5. Recently, researchers examining epigenetic transmission have begun to apply genome-wide approaches. In humans, reduced representation bisulfite sequencing (RRBS) was performed on peripheral samples that were obtained from individuals who were prenatally exposed to the “Dutch Hunger Winter”, resulting in two Differentially Methylated Regions (DMRs) in INSR and CPTIA genes that were functionally, biologically and technically validated, and significantly associated with birth weights and LDL cholesterol levels in offspring. In rodents, non-genomic intergenerational transmission of anxiety which was associated with differentially methylated enhancers that were putatively involved in lipid signaling and synaptic/neurotransmission in hippocampal granule cells, was discovered also using RRBS. Finally, transgenerational transmission of altered behaviors was associated with sperm-derived microRNAs produced by ELS male mice. The field of epigenetic transmission is just beginning to enter the epigenomic era by using genome-wide analyses. Such approaches remain of strong interest to human studies, first in order to help to assess the relevance of the previous targeted studies, and second to discover new important epigenetic modifications of potential clinical importance. New discoveries may help to assess how transmittable the negative impact of stress may be to offspring. The latter may open doors for future treatments and resilience-promoting interventions, as well as new approaches to treat the effects of childhood trauma before the onset of psychiatric disorder.

Background: Adverse Childhood Experiences (ACEs), which include traumatic injury, are associated with poor health outcomes in later life, yet the biological mechanisms mediating this association are unknown. Neurocircuitry, immune system and hormone regulation differ from normal in adults reporting ACEs. These systems could be affected by epigenetic changes, including methylation of cytosine (5mC) in genomic DNA, activated by ACEs. Since 5mC levels influence gene expression and can be long-lasting, altered 5mC status at specific sites or throughout the genome is hypothesized to influence mental and physical outcomes after ACE(s). Human and animal studies support this, with animal models allowing experiments for attributing causality. Here we provide a lengthy introduction and background on 5mC and the impact of early life adversity. Objective: Next we address the issue of a mixture of cell types in saliva, the most accessible biospecimen for 5mC analysis. Typical human bio-specimens for 5mC analysis include saliva or buccal swabs, whole blood or types of blood cells, tumors and post-mortem brain. In children saliva is the most accessible biospecimen, but contains a mixture of keratinocytes and white blood cells, as do buccal swabs. Even in saliva from the same individual at different time points, cell composition may differ widely. Similar issues affect analysis in blood, where nucleated cells represent a wide array of white blood cell types. Unless variations in ratios of these cells between each sample are included in the analysis, results can be unreliable. Methods: Several different biochemical assays are available to test for site-specific methylation levels genome- wide, each producing different information, with high-density arrays being the easiest to use, and bisulfite whole genome sequencing the most comprehensive. We compare results from different assays and use high-throughput computational processing to deconvolve cell composition in saliva samples. Results: Here we present examples demonstrating the critical importance of determining the relative contribution of blood cells versus keratinocytes to the 5mC profile found in saliva. We further describe a strategy to perform a reference-based computational correction for cell composition, and therefore to identify differential methylation patterns due to experience, or for the diagnosis of phenotypes that correlate between traits, such as hormone levels, trauma status and various mental health outcomes. Conclusion: Specific sites that respond to adversity with altered methylation levels in either blood cells, keratinocytes or both can be identified by this rigorous approach, which will then be useful as diagnostic biomarkers and therapeutic targets.

The routine therapeutic use of antibiotics has caused resistance genes to be disseminated across microbial populations. In particular, bacterial strains having antibiotic resistance genes are frequently observed in the human microbiome. Moreover, multidrug-resistant pathogens are now widely spread, threatening public health. Such genes are transferred and spread among bacteria even in different environments. Advances in high throughput sequencing technology and computational algorithms have accelerated investigation into antibiotic resistance genes of bacteria. Such studies have revealed that the antibiotic resistance genes are located close to the mobility-associated genes, which promotes their dissemination. An increasing level of information on genomic sequences of resistome should expedite research on drug-resistance in our body and environment, thereby contributing to the development of public health policy. In this review, the high prevalence of antibiotic resistance genes and their exchange in the human and environmental microbiome is discussed with respect to the genomic contents. The relationships among diverse resistomes, related bacterial species, and the antibiotics are reviewed. In addition, recent advances in bioinformatics approaches to investigate such relationships are discussed.

In nature, microbes do not exist in isolation but co-exist in a variety of ecological and biological environments and on various host organisms. Due to their close proximity, these microbes interact among themselves, and also with the hosts in both positive and negative manners. Moreover, these interactions may modulate dynamically upon external stimulus as well as internal community changes. This demands systematic techniques such as mathematical modeling to understand the intrinsic community behavior. Here, we reviewed various approaches for metabolic modeling of microbial communities. If detailed species-specific information is available, segregated models of individual organisms can be constructed and connected via metabolite exchanges; otherwise, the community may be represented as a lumped network of metabolic reactions. The constructed models can then be simulated to help fill knowledge gaps, and generate testable hypotheses for designing new experiments. More importantly, such community models have been developed to study microbial interactions in various niches such as host microbiome, biogeochemical and bioremediation, waste water treatment and synthetic consortia. As such, the metabolic modeling efforts have allowed us to gain new insights into the natural and synthetic microbial communities, and design interventions to achieve specific goals. Finally, potential directions for future development in metabolic modeling of microbial communities were also discussed.

A major biological challenge in the postgenomic era has been untangling the composition and functions of microbes that inhabit complex communities or microbiomes. Multi-omics and modern bioinformatics have provided the tools to assay molecules across different cellular and community scales; however, mechanistic knowledge over microbial interactions often remains elusive. This is due to the immense diversity and the essentially undiminished volume of not-yet-cultured microbes. Simplified model communities hold some promise in enabling researchers to manage complexity so that they can mechanistically understand the emergent properties of microbial community interactions. In this review, we surveyed several approaches that have effectively used tractable model consortia to elucidate the complex behavior of microbial communities. We go further to provide some perspectives on the limitations and new opportunities with these approaches and highlight where these efforts are likely to lead as advances are made in molecular ecology and systems biology.