Biology subjects

Hofmann, H. A.

Publications and source records attributed to Hofmann, H. A..

25 records · Page 2Linked to original sources

bioRxiv2019

Molecular Profiling to Infer Neuronal Cell Identity: Lessons from small ganglia of the Crab Cancer borealis

Understanding circuit organization depends on identification of cell types. Recent advances in transcriptional profiling methods have enabled classification of cell types by their gene expression. While exceptionally powerful and high throughput, the ground-truth validation of these methods is difficult: if cell type is unknown, how does one assess whether a given analysis accurately captures neuronal identity? To shed light on the capabilities and limitations of solely using transcriptional profiling for cell type classification, we performed two forms of transcriptional profiling - RNA-seq and quantitative RT-PCR, in single, unambiguously identified neurons from two small crustacean networks: the stomatogastric and cardiac ganglia. We then combined our knowledge of cell type with unbiased clustering analyses and supervised machine learning to determine how accurately functionally-defined neuron types can be classified by expression profile alone. Our results demonstrate that expression profile is able to capture neuronal identity most accurately when combined with multimodal information that allows for post-hoc grouping so analysis can proceed from a supervised perspective. Solely unsupervised clustering can lead to misidentification and an inability to distinguish between two or more cell types. Therefore, our study supports the general utility of cell identification by transcriptional profiling, but adds a caution: it is difficult or impossible to know under what conditions transcriptional profiling alone is capable of assigning cell identity. Only by combining multiple modalities of information such as physiology, morphology or innervation target can neuronal identity be unambiguously determined.\n\nSIGNIFICANCE STATEMENTSingle cell transcriptional profiling has become a widespread tool in cell identification, particularly in the nervous system, based on the notion that genomic information determines cell identity. However, many cell type classification studies are unconstrained by other cellular attributes (e.g., morphology, physiology). Here, we systematically test how accurately transcriptional profiling can assign cell identity to well-studied anatomically- and functionally-identified neurons in two small neuronal networks. While these neurons clearly possess distinct patterns of gene expression across cell types, their expression profiles are not sufficient to unambiguously confirm their identity. We suggest that true cell identity can only be determined by combining gene expression data with other cellular attributes such as innervation pattern, morphology, or physiology.

neuroscience↗

bioRxiv2018

A tagging method for very small fish

Identifying individuals over time and across contexts is essential in many scientific fields. There are a variety of well-established methods for uniquely marking individuals (e.g., visible implant elastomer, barcodes, paint). However, for some species, life history stages, and/or experiments, existing methods are not sufficient. Here, we describe procedures for how two tagging methods - a tattoo ink injection method and a fishing line piercing method - can be used with the youngest, smallest juveniles of the African cichlid fish, Astatotilapia burtoni, which are too small for the methods used with adults. With the tattoo method, we injected tattoo ink into the dorsal muscle. Different colors and injection locations can be used to distinguish among individuals over a period of weeks (up to 4 weeks, average 2.5-3 weeks under our conditions). Because fish this young and small are sensitive to handling and injection, we also include physiological data showing fish recover well from anesthetization and tagging. With the piercing method, very thin fishing line is threaded through the dorsal muscle and tied into a barbell or loop. Unique colors and patterns can be used to distinguish among individuals over a period of months. Because a physical tag might impede normal movement in a very small fish, we also include data from an open field exploration test showing similar behavior between tagged and control (non-tagged) juveniles. We expect these effective and inexpensive methods to be useful for a variety of small species and will facilitate early-life, developmental, and longitudinal research.

animal behavior and cognition↗

bioRxiv2018

Early-life social environment alters juvenile behavior and neuroendocrine function in a highly social cichlid fish

Early-life experiences can shape adult behavior, with consequences for fitness and health, yet fundamental questions remain unanswered about how early-life social experiences are translated into variation in brain and behavior. The African cichlid fish Astatotilapia burtoni, a model system in social neuroscience, is well known for its highly plastic social phenotypes in adulthood. Here, we rear juveniles in either social groups or pairs to investigate the effects of early-life social environments on behavior and neuroendocrine gene expression. We find that both juvenile behavior and neuroendocrine function are sensitive to early-life effects. Behavior robustly co-varies across multiple contexts (open field, social cue investigation, and dominance behavior assays) to form a behavioral syndrome, with pair-reared juveniles towards the end of syndrome that is less active and socially interactive. Pair-reared juveniles also submit more readily as subordinates. In a separate cohort, we measured whole brain expression of stress and sex hormone genes. Expression of glucocorticoid receptor (GR) 1a was elevated in group-reared juveniles, supporting a highly-conserved role for the stress axis mediating early-life effects. The effect of rearing environment on androgen receptor (AR) and estrogen receptor (ER) expression was mediated by treatment duration (1 vs. 5 weeks). Finally, expression of corticotropin-releasing factor (CRF) and GR2 decreased significantly over time. Rearing environment also caused striking differences in gene co-expression, such that expression was tightly integrated in pair-reared juveniles, but not group-reared or isolates. Together, this research demonstrates the important developmental origins of behavioral phenotypes and identifies potential behavioral and neuroendocrine mechanisms.

neuroscience↗

bioRxiv2017

Analysis of hippocampal transcriptomic responses to technical and biological perturbations

Cost-effective next-generation sequencing has made unbiased gene expression analysis possible. Single-neuron gene expression studies may be especially important for understanding nervous system structure and function because of the neuron-specific functionality and plasticity that defines functional neural circuits. Cellular dissociation is a prerequisite technical manipulation for single-cell and single cell-population studies, but the extent to which the cellular dissociation process cells affects neural gene expression has not been determined, nor has it been determined how gene expression is altered by the stress that accompanies many of the behavioral manipulations that are required to study learning and memory and other cognitive functions. Here, we determined to which extent cellular dissociation-induced changes in hippocampal gene expression might confound studies on the behavioral and physiological functions of the hippocampus. We processed tissue punch samples from the dentate gyrus (DG), CA3, and CA1 hippocampus subfields using either a tissue homogenization protocol or a cellular dissociation protocol in preparation for RNA sequencing analysis to evaluate the impact of the tissue preparation. Then, we evaluated the effect of stressful experience and cognitive training on hippocampus subfield specific gene expression and determined to which extent these response overlap with the cellular dissociation response. Finally, we assessed the extent to which the subfield-specific gene expression patterns are consistent with those identified in a recently published hippocampus subfield-specific gene expression database. We report substantial differences in baseline subfield-specific gene expression, that 1% of the hippocampal transcriptome is altered by the process of cellular dissociation, that an even weaker alteration is detected 24 h after stressful experience, and that while these alterations are largely distinct from the subfield specific response of the hippocampus transcriptome to cognitive training, there is nonetheless some important confounding overlap. These findings of the concordant and discordant effects of technical and behavioral manipulations should inform the design of future neural transcriptome studies and thus facilitate a more comprehensive understanding of hippocampal function.

neuroscience↗

bioRxiv2017

SArKS: Discovering Gene Expression Regulatory Motifs And Domains By Suffix Array Kernel Smoothing

MotivationWe set out to develop an algorithm that can mine differential gene expression data to identify candidate cell type-specific DNA regulatory sequences. Differential expression is usually quantified as a continuous score--fold-change, test-statistic, p-value--comparing biological classes. Unlike existing approaches, our de novo strategy, termed SArKS, applies nonparametric kernel smoothing to uncover promoter motifs that correlate with elevated differential expression scores. SArKS detects motifs by smoothing sequence scores over sequence similarity. A second round of smoothing over spatial proximity reveals multi-motif domains (MMDs). Discovered motifs can then be merged or extended based on adjacency within MMDs. False positive rates are estimated and controlled by permutation testing.\n\nResultsWe applied SArKS to published gene expression data representing distinct neocortical neuron classes in M. musculus and interneuron developmental states in H. sapiens. When benchmarked against several existing algorithms for correlative motif discovery using a cross-validation procedure, SArKS identified larger motif sets that formed the basis for regression models with higher correlative power.\n\nAvailabilityhttps://github.com/denniscwylie/sarks.\n\nContactdenniswylie@austin.utexas.edu.\n\nSupplementary informationappended to document.

bioinformatics↗

bioRxiv2017

Evolution of Animal Neural Systems

Nervous systems are one of the most spectacular products of evolution. Their provenance and evolution have been an area of interest and often intense debate since the late 19th century. The genomics era has provided researchers with a new set of tools with which to study the early evolution of neurons, and recent progress on the molecular evolution of the first neurons has been both exciting and frustrating. It has become increasingly obvious that genomic data is often insufficient to reconstruct complex phenotypes in deep evolutionary time. We review this recent progress and its attendant challenges, and suggest ways forward.

evolutionary biology↗

bioRxiv2017

Single-Neuron Gene Expression Analysis Using the Maxwell 16 LEV System in the Neural Systems and Behavior Course

Gene expression analysis from single cells has become increasingly prominent across biological disciplines; thus, it is important to train students in these approaches. Here, we present an experimental and analysis pipeline that we developed for the Neural Systems & Behavior (NS&B) course at Marine Biological Laboratory. Our approach used the Maxwell(R) 16 LEV simplyRNA Tissue Kit and GoTaq(R) 2-Step RT-qPCR System for gene expression analysis from single neurons of the crustacean stomatogastric ganglion, a model system to study the generation of rhythmic motor patterns. We used double-stranded RNA to knockdown expression of a putative neuromodulator-activated sodium channel. We then examined the electrophysiological responses to known neuromodulators and confirmed that the response was reduced. Finally, we measured how mRNA levels of several ion channel genes changed in response. Our results provide new insights into the neural mechanisms underlying the generation and modulation of rhythmic motor patterns.

neuroscience↗