Publications

V(D)J recombination relies on the presence of proximal enhancers that activate the antigen receptor (AgR) loci in a lineage- and stage-specific manner. Unexpectedly, we find that both active and inactive AgR enhancers cooperate to disseminate their effects in a localized and long-range manner. Here, we demonstrate the importance of short-range contacts between active enhancers that constitute an Igk super-enhancer in B cells. Deletion of one element reduces the interaction frequency between other enhancers in the hub, which compromises the transcriptional output of each component. Furthermore, we establish that, in T cells, long-range contact and cooperation between the inactive Igk enhancer MiEκ and the active Tcrb enhancer Eβ alters enrichment of CBFβ binding in a manner that impacts Tcrb recombination. These findings underline the complexities of enhancer regulation and point to a role for localized and long-range enhancer-sharing between active and inactive elements in lineage- and stage-specific control.

Selecting regularization parameters in penalized high-dimensional graphical models in a principled, data-driven, and computationally efficient manner continues to be one of the key challenges in high-dimensional statistics. We present substantial computational gains and conceptual generalizations of the Stability Approach to Regularization Selection (StARS), a state-of-the-art graphical model selection scheme. Using properties of the Poisson-Binomial distribution and convex non-asymptotic distributional modeling we propose lower and upper bounds on the StARS graph regularization path which results in greatly reduced computational cost without compromising regularization selection. We also generalize the StARS criterion from single edge to induced subgraph (graphlet) stability. We show that simultaneously requiring edge and graphlet stability leads to superior graph recovery performance independent of graph topology. These novel insights render Gaussian graphical model selection a routine task on standard multi-core computers.

The zebra finch brain features a set of clearly defined and hierarchically arranged motor nuclei that are selectively responsible for producing singing behavior. One of these regions, a critical forebrain structure called HVC, contains premotor neurons that are active at precise time points during song production. However, the neural representation of this behavior at a population level remains elusive. We used two-photon microscopy to monitor ensemble activity during singing, integrating across multiple trials by adopting a Bayesian inference approach to more precisely estimate burst timing. Additionally, we examined spiking and motor-related synaptic inputs using intracellular recordings during singing. With both experimental approaches, we find that premotor events do not occur preferentially at the onsets or offsets of song syllables or at specific subsyllabic motor landmarks. These results strongly support the notion that HVC projection neurons collectively exhibit a temporal sequence during singing that is uncoupled from ongoing movements.

Background

The throughput of electrophysiological recording is growing rapidly, allowing thousands of simultaneous channels, and there is a growing variety of spike sorting algorithms designed to extract neural firing events from such data. This creates an urgent need for standardized, automatic evaluation of the quality of neural units output by such algorithms.

New method

We introduce a suite of validation metrics that assess the credibility of a given automatic spike sorting algorithm applied to a given dataset. By rerunning the spike sorter two or more times, the metrics measure stability under various perturbations consistent with variations in the data itself, making no assumptions about the internal workings of the algorithm, and minimal assumptions about the noise.

Results

We illustrate the new metrics on standard sorting algorithms applied to both in vivo and ex vivo recordings, including a time series with overlapping spikes. We compare the metrics to existing quality measures, and to ground-truth accuracy in simulated time series. We provide a software implementation.
Comparison with existing methods

Metrics have until now relied on ground-truth, simulated data, internal algorithm variables (e.g. cluster separation), or refractory violations. By contrast, by standardizing the interface, our metrics assess the reliability of any automatic algorithm without reference to internal variables (e.g. feature space) or physiological criteria.
Conclusions

Stability is a prerequisite for reproducibility of results. Such metrics could reduce the significant human labor currently spent on validation, and should form an essential part of large-scale automated spike sorting and systematic benchmarking of algorithms.

Increasing incidence of inflammatory bowel diseases, such as Crohn’s disease, in developed nations is associated with changes to the microbial environment, such as decreased prevalence of helminth colonization and alterations to the gut microbiota. We find that helminth infection protects mice deficient in the Crohn’s disease susceptibility gene Nod2 from intestinal abnormalities by inhibiting colonization by an inflammatory Bacteroides species. Resistance to Bacteroides colonization was dependent on type 2 immunity, which promoted the establishment of a protective microbiota enriched in Clostridiales. Additionally, we show that individuals from helminth-endemic regions harbor a similar protective microbiota and that deworming treatment reduced levels of Clostridiales and increased Bacteroidales. These results support a model of the hygiene hypothesis in which certain individuals are genetically susceptible to the consequences of a changing microbial environment.

Connectivity patterns of neocortex exhibit several odd properties: for example, most neighboring excitatory neurons do not connect, which seems curiously wasteful. Brunel’s elegant theoretical treatment reveals how optimal information storage can naturally impose these peculiar properties.

Connectivity patterns of neocortex exhibit several odd properties: for example, most neighboring excitatory neurons do not connect, which seems curiously wasteful. Brunel’s elegant theoretical treatment reveals how optimal information storage can naturally impose these peculiar properties.

Our brains analyze high-dimensional datasets streamed by our sensory organs in multiple stages. Sensory cortices, for example, perform tasks like dimensionality reduction, sparse feature discovery and clustering. To model these tasks we pursue an approach analogous to use of action principles in physics and propose a new family of objective functions based on the principle of similarity matching. From these objective functions we derive online distributed algorithms that can be implemented by biological neural networks resembling cortical circuits. Our networks can adapt to changes in the number of latent dimensions or the number of clusters in the input dataset. Furthermore, we formulate minimax optimization problems from which we derive online algorithms with two classes of neurons identified with principal neurons and interneurons in biological circuits. In addition to bearing resemblance to biological circuits, our algorithms are competitive for Big Data applications.

The past decade has witnessed a rapid rise in the use of social media around the globe. 1
For political scientists, this is a phenomenon begging to be understood. It has been claimed
repeatedly–usually in the absence of solid data–that these social media resources are
profoundly shaping participation in social movements, including protest movements (see
Bond, Fariss, Jones, Kramer, Marlow, Settle, & Fowler 2012; Cha et al. 2010; Jungherr,
Jurgens, & Schoen 2012; Lynch 2011; Shirky 2011). Social media are often assumed to affect an extremely wide range of individual-level behaviors, including communicating about politics to friends and family members, donating or soliciting money for political campaigns and causes, voting, and engaging in collective forms of protest. In truth, however, the research community knows remarkably little about whether (and especially how) the use of social media systematically affects political participation.

Immunoglobulin (Ig) class switch recombination (CSR) is initiated by the transcription-coupled recruitment of activation-induced cytidine deaminase (AID) to Ig switch regions (S regions). During CSR, the IgH locus undergoes dynamic three-dimensional structural changes in which promoters, enhancers, and S regions are brought to close proximity. Nevertheless, little is known about the underlying mechanisms. In this study, we show that Med1 and Med12, two subunits of the mediator complex implicated in transcription initiation and long-range enhancer/promoter loop formation, are dynamically recruited to the IgH locus enhancers and the acceptor regions during CSR and that their knockdown in CH12 cells results in impaired CSR. Furthermore, we show that conditional inactivation of Med1 in B cells results in defective CSR and reduced acceptor S region transcription. Finally, we show that in B cells undergoing CSR, the dynamic long-range contacts between the IgH enhancers and the acceptor regions correlate with Med1 and Med12 binding and that they happen at a reduced frequency in Med1-deficient B cells. Our results implicate the mediator complex in the mechanism of CSR and are consistent with a model in which mediator facilitates the long-range contacts between S regions and the IgH locus enhancers during CSR and their transcriptional activation.

Ig class switch recombination (CSR) is a long-range DNA recombination reaction that occurs between Ig switch regions (S regions) and that replaces the isotype expressed (from IgM to IgG, IgE, or IgA), providing novel effector functions for efficient antigen clearance (Chaudhuri et al., 2007). CSR is initiated by the transcription-coupled recruitment of activation-induced cytidine deaminase (AID; Basu et al., 2011; Pavri and Nussenzweig, 2011), an enzyme that deaminates cytosines into uracils in the single-strand DNA exposed by transcription (Petersen-Mahrt et al., 2002). During CSR, the choice of recombination to a particular isotype is determined by the activation of specific S region promoters (Basu et al., 2011; Pavri and Nussenzweig, 2011), triggering the generation of noncoding germline transcripts (Chaudhuri et al., 2007). Germline transcription precedes recombination, is induced at both the donor and acceptor S regions, and is required for recombination (Chaudhuri et al., 2007). Transcriptional activation of the IgH locus during CSR is controlled by the Eμ enhancer located upstream of the donor (Sμ) S region and by a major regulatory region (RR) located at the 3′ end of the locus (3′ RR). Both of these enhancer elements are required for transcription and for CSR (Chaudhuri et al., 2007; Pavri and Nussenzweig, 2011). The current model is that during CSR, recombination between S regions proceeds by the inducible formation of long-range DNA loops involving the S region promoters and the Eμ and 3′ RR enhancers (Wuerffel et al., 2007; Kenter et al., 2012), possibly through transcription factors (Feldman et al., 2015). Nevertheless, the molecular mechanisms controlling these conformational changes remain to be elucidated.

Mediator is an evolutionarily conserved multiprotein complex composed of 31 subunits organized in four modules that is required for gene transcription by RNA polymerase II (Pol II; Malik and Roeder, 2010; Conaway and Conaway, 2011). The head, middle, and tail modules form a stable core complex that associates reversibly with the CDK8 module (consisting of cyclin-dependent kinase 8, cyclin C, Med12, and Med13) to control interactions of mediator with the Pol II machinery (Malik and Roeder, 2010; Conaway and Conaway, 2011). Mediator behaves as an interface between Pol II and transcription factors and is capable of promoting Pol II preinitiation complex assembly, transcription initiation by Pol II, regulation of Pol II pausing and elongation, recruitment of transcription elongation factors, and control of the phosphorylation state of the C-terminal domain of Pol II (Malik and Roeder, 2010; Conaway and Conaway, 2011; Allen and Taatjes, 2015). The Med1 subunit of mediator, part of the middle module, interacts with distinct transcriptional activators (Borggrefe and Yue, 2011) and has been shown to play a key role in embryonic development (Ito et al., 2000; Zhu et al., 2000), erythropoiesis (Stumpf et al., 2010), and iNKT cell development (Yue et al., 2011). In addition, Med1 recruitment to chromatin is one of the features that characterizes super enhancers (Whyte et al., 2013). Interestingly, mediator has also been implicated, together with cohesin, in the formation of long-range DNA loops (Malik and Roeder, 2010; Conaway and Conaway, 2011; Allen and Taatjes, 2015), and chromatin immunoprecipitation sequencing (ChIP-Seq) analysis for Smc1, Smc3, Med1, and Med12 revealed that cohesin–mediator binding predicts genomic sites of long-range promoter–enhancer interactions (Kagey et al., 2010; Phillips-Cremins et al., 2013). As we have recently implicated the cohesin complex in the mechanism of CSR (Thomas-Claudepierre et al., 2013), we have examined the role of mediator in CSR by performing shRNA-mediated knockdowns of the Med1 and Med12 subunits of mediator (belonging to different modules) in CH12 cells and by conditionally inactivating the Med1 subunit in developing B cells.