It is generally believed that associative memory in the brain depends on multistable synaptic dynamics, which enable the synapses to maintain their value for extended periods of time. However, multistable dynamics are not restricted to synapses. In particular, the dynamics of some genetic regulatory networks are multistable, raising the possibility that even single cells, in the absence of a nervous system, are capable of learning associations. Here we study a standard genetic regulatory network model with bistable elements and stochastic dynamics. We demonstrate that such a genetic regulatory network model is capable of learning multiple, general, overlapping associations. The capacity of the network, defined as the number of associations that can be simultaneously stored and retrieved, is proportional to the square root of the number of bistable elements in the genetic regulatory network. Moreover, we compute the capacity of a clonal population of cells, such as in a colony of bacteria or a tissue, to store associations. We show that even if the cells do not interact, the capacity of the population to store associations substantially exceeds that of a single cell and is proportional to the number of bistable elements. Thus, we show that even single cells are endowed with the computational power to learn associations, a power that is substantially enhanced when these cells form a population.

SummaryEmbryonic stem cells (ESCs), with their dual capacity to self-renew and differentiate, are commonly used to study differentiation, epigenetic regulation, lineage choices, and more. Using non-directed retroviral integration of a YFP/Cherry exon into mouse ESCs, we generated a library of over 200 endogenously tagged fluorescent fusion proteins and present several proof-of-concept applications of this library. We show the utility of this library to track proteins in living cells; screen for pluripotency-related factors; identify heterogeneously expressing proteins; measure the dynamics of endogenously labeled proteins; track proteins recruited to sites of DNA damage; pull down tagged fluorescent fusion proteins using anti-Cherry antibodies; and test for interaction partners. Thus, this library can be used in a variety of different directions, either exploiting the fluorescent tag for imaging-based techniques or utilizing the fluorescent fusion protein for biochemical pull-down assays, including immunoprecipitation, co-immunoprecipitation, chromatin immunoprecipitation, and more.

The human genome contains dozens of genes that encode for proteins containing long poly-glutamine repeats (polyQ, usually encoded by CAG codons) of 10Qs or more. However, only nine of these genes have been reported to expand beyond the healthy variation and cause diseases. To address whether these nine disease-associated genes are unique in any way, we compared genetic and epigenetic features relative to other types of genes, especially repeat containing genes that do not cause diseases. Our analyses show that in pluripotent cells, the nine polyQ disease-related genes are characterized by an open chromatin profile, enriched for active chromatin marks and depleted for suppressive chromatin marks. By contrast, genes that encode for polyQ-containing proteins that are not associated with diseases, and other repeat containing genes, possess a suppressive chromatin environment. We propose that the active epigenetic landscape support decreased genomic stability and higher susceptibility for expansion mutations.

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In the earliest step of spliceosome assembly, the two splice sites flanking an intron are brought into proximity by U1 snRNP and U2AF along with other proteins. The mechanism that facilitates this intron looping is poorly understood. Using a CRISPR interference-based approach to halt RNA polymerase II transcription in the middle of introns in human cells, we discovered that the nascent 5′ splice site base pairs with a U1 snRNA that is tethered to RNA polymerase II during intron synthesis. This association functionally corresponds with splicing outcome, involves bona fide 5′ splice sites and cryptic intronic sites, and occurs transcriptome-wide. Overall, our findings reveal that the upstream 5′ splice sites remain attached to the transcriptional machinery during intron synthesis and are thus brought into proximity of the 3′ splice sites; potentially mediating the rapid splicing of long introns.

Transposable elements (TEs) are induced in response to viral infections. TEs induction triggers a robust and durable interferon (IFN) response, providing a host defense mechanism. Still, the connection between SARS-CoV-2 IFN response and TEs remained unexplored. Here, we analyzed TE expression changes in response to SARS-CoV-2 infection in different human cellular models. We find that compared to other viruses, which cause global upregulation of TEs, SARS-CoV-2 infection results in a significantly milder TE response in both primary lung epithelial cells and in iPSC-derived lung alveolar type 2 cells. In general, we observe that TE activation correlates with, and precedes, the induction of IFN-related genes, suggesting that the failure to activate TEs may be the reason for the weak IFN response. Moreover, we identify two variables which explain most of the observed diverseness in immune responses: basal expression levels of TEs in the pre-infected cell, and the viral load. Since basal TE levels increase with age, we propose that "TE desensitization" leads to age-related death from COVID19. This work provides a potential mechanistic explanation for SARS-CoV-2s success in its fight against the host immune system, and suggests that TEs could be used as sensors or serve as potential drug targets for COVID-19.

Emerging evidence shows that transposable elements (TEs) are induced in response to viral infections. This TE induction is suggested to trigger a robust and durable interferon response, providing a host defense mechanism. Here, we analyze TE expression changes in response to SARS-CoV-2 infection in different human cellular models. Unlike other viruses, SARS-CoV-2 infection does not lead to global upregulation of TEs in primary cells. We report a correlation between TEs activation and induction of interferon-related genes, suggesting that failure to activate TEs may account for the weak interferon response. Moreover, we identify two variables that explain most of the observed diverseness in immune responses: basal expression levels of TEs in the pre-infected cells and the viral load. Finally, analyzing the SARS-CoV-2 interactome and the epigenetic landscape around the TEs activated following infection, we identify SARS-CoV-2 interacting proteins, which may regulate chromatin structure and TE transcription. This work provides a possible functional explanation for SARS-CoV-2 success in its fight against the host immune system and suggests that TEs could serve as potential drug targets for COVID-19.

Background Many neurodegenerative diseases develop only later in life, when cells in the nervous system lose their structure or function. In many forms of neurodegenerative diseases, this late-onset phenomenon remains largely unexplained. Results Analyzing single-cell RNA sequencing from Alzheimer’s disease (AD) and Huntington’s disease (HD) patients, we find increased transcriptional heterogeneity in disease-state neurons. We hypothesize that transcriptional heterogeneity precedes neurodegenerative disease pathologies. To test this idea experimentally, we use juvenile forms (72Q; 180Q) of HD iPSCs, differentiate them into committed neuronal progenitors, and obtain single-cell expression profiles. We show a global increase in gene expression variability in HD. Autophagy genes become more stable, while energy and actin-related genes become more variable in the mutant cells. Knocking down several differentially variable genes results in increased aggregate formation, a pathology associated with HD. We further validate the increased transcriptional heterogeneity in CHD8+/− cells, a model for autism spectrum disorder. Conclusions Overall, our results suggest that although neurodegenerative diseases develop over time, transcriptional regulation imbalance is present already at very early developmental stages. Therefore, an intervention aimed at this early phenotype may be of high diagnostic value.