Biology subjects

Goyal, S.

Publications and source records attributed to Goyal, S..

45 records · Page 3Linked to original sources

bioRxiv2021

Revealing cell-fate bifurcations from transcriptomic trajectories of hematopoiesis

Inspired by Waddingtons illustration of an epigenetic landscape, cell-fate transitions have been envisioned as bifurcating dynamical systems, wherein the dynamics of an exogenous signal couples to a cells enormously complex signaling and transcriptional machinery, eliciting a qualitative transition in the collective state of a cell - its fate. It remains unclear, however, whether the dynamical systems framework can go beyond a word-based caricature of the system and provide sharp quantitative insights that further our understanding of differentiation. Single-cell RNA sequencing (scRNA-seq), which measures the distributions of possible transcriptional states in large populations of differentiating cells, provides an alternate view, in which development is marked by the individual concentration variations of a myriad of genes. Here, starting from formal mathematical derivations, we challenge these transcriptomic trajectories to a rigorous statistical evaluation of whether they display signatures consistent with bifurcations. After pinpointing bifurcations along transcriptomic trajectories of the neutrophil branch of hematopoeitic differentiation we are able to further leverage the primitive features of a linear instability to identify the single-direction in gene expression space along which the bifurcation unfolds and identify possible gene contributors. This scheme identifies transcription factors long viewed to play a crucial role in the process of neutrophil differentiation in addition to identifying a host of other novel genetic players. Most broadly speaking, we provide evidence that, though very high-dimensional, a bifurcating dynamical systems formalism might be appropriate for the process of cellular differentiation and that it can be leveraged to provide insights. Ambitiously, our work attempts to take a step beyond data-analysis and towards the construction of falsifiable mathematical models that describe the dynamics of the entire transcriptome.

biophysics↗

bioRxiv2020

Inferring metabolic rewiring in embryonic neural development using single cell data

Metabolism is intricately linked with cell fate changes. Much of this understanding comes from detailed metabolomics studies averaged across a population of cells which may be composed of multiple cell types. Currently, there are no quantitative techniques sensitive enough to assess metabolomics broadly at the single cell level. Here we present scMetNet, a technique that interrogates metabolic rewiring at the single cell resolution and we apply it to murine embryonic development. Our method first confirms the key metabolic pathways, categorized into bioenergetic, epigenetic and biosynthetic, that change as embryonic neural stem cells differentiate and age. It then goes beyond to identify specific sub-networks, such as the cholesterol and mevalonate biosynthesis pathway, that drive the global metabolic changes during neural cortical development. Having such contextual information about metabolic rewiring provides putative mechanisms driving stem cell differentiation and identifies potential targets for regulating neural stem cell and neuronal biology.

systems biology↗

bioRxiv2020

Flapping, swirling and flipping: Non-linear dynamics of pre-stressed active filaments

Initially straight slender elastic filaments and rods with geometrically constrained ends buckle and form stable two-dimensional shapes when compressed by bringing the ends together. It is known that beyond a critical value of this pre-stress, clamped rods transition to bent, twisted three-dimensional equilibrium shapes. Here, we analyze the three-dimensional instabilities and dynamics of such pre-stressed, initially twisted filaments subject to active follower forces and dissipative fluid drag. We find that degree of boundary constraint and the directionality of active forces determines if oscillatory instabilities can arise. When filaments are clamped at one end and pinned at the other with follower forces directed towards the clamped end, stable planar flapping oscillations result; reversing the directionality of the active forces quenches the instability. When both ends are clamped however, computations reveal a novel secondary instability wherein planar oscillations are destabilized by off-planar perturbations resulting in three-dimensional swirling patterns with periodic flips. These swirl-flip transitions are characterized by two distinct and time-scales. The first corresponds to unidirectional swirling rotation around the end-to-end axis. The second captures the time between flipping events when the direction of swirling reverses. We find that this spatiotemporal dance resembles relaxation oscillations with each cycle initiated by a sudden jump in torsional deformation and then followed by a period of gradual decrease in net torsion until the next cycle of variations. Our work reveals the rich tapestry of spatiotemporal patterns when weakly inertial strongly damped rods are deformed by non-conservative active forces. Practically, our results suggest avenues by which pre-stress, elasticity and activity may be used to design synthetic fluidic elements to pump or mix fluid at macroscopic length scales.

biophysics↗

bioRxiv2020

Thioesterase Superfamily Member 1 Undergoes Stimulus-coupled Reorganization to Regulate Metabolism

In brown adipose tissue, cold exposure promotes thermogenesis, in large part by increasing mitochondrial {beta}-oxidation of lipid droplet-derived fatty acids. This process is suppressed by thioesterase superfamily member 1 (Them1), a long chain fatty acyl-CoA thioesterase that is highly upregulated by cold ambient temperatures. Them1 reduces fatty acid availability for {beta}-oxidation in mitochondria and limits thermogenesis by cellular mechanisms that are not well defined. We show that Them1 regulates metabolism by undergoing marked intracellular conformational changes that occur in response to {beta}-adrenergic stimulation. Mechanistically, Them1 formed puncta that were localized near LD and mitochondria in an immortalized brown adipose cell line. In response to stimulation by norepinephrine, Them1 was phosphorylated by PKC{beta} at S15, which specifically inhibited puncta formation and resulted in a diffuse intracellular localization. This change in Them1 localization also occurred after stimulation in vivo. Puncta formation activated Them1 metabolic activity in vitro, as evidenced by suppression of oxygen consumption following {beta}-adrenergic stimulation. We show by correlative light and electron microscopy that puncta are biomolecular condensates (also known as membraneless organelles) that typically form by phase separation. Them1 contains one intrinsically disordered region at the N-terminus with multiple interacting motifs that is frequently observed in phase-separating proteins. Phosphorylation, which is known to disrupt phase separation and aggregation, results in a diffuse Them1 localization. Our data thus establish that Them1 forms intracellular biomolecular condensates that limit fatty acid oxidation and suppress thermogenesis. During a period of energy demand, the condensates are disrupted by phosphorylation to allow for maximal thermogenesis. The stimulus-coupled reorganization of Them1 thus provides fine-tuning of thermogenesis and energy expenditure.

cell biology↗

bioRxiv2019

Biological Structure and Function Emerge from Scaling Unsupervised Learning to 250 Million Protein Sequences

In the field of artificial intelligence, a combination of scale in data and model capacity enabled by un-supervised learning has led to major advances in representation learning and statistical generation. In the life sciences, the anticipated growth of sequencing promises unprecedented data on natural sequence diversity. Protein language modeling at the scale of evolution is a logical step toward predictive and generative artificial intelligence for biology. To this end we use unsupervised learning to train a deep contextual language model on 86 billion amino acids across 250 million protein sequences spanning evolutionary diversity. The resulting model contains information about biological properties in its representations. The representations are learned from sequence data alone. The learned representation space has a multi-scale organization reflecting structure from the level of biochemical properties of amino acids to remote homology of proteins. Information about secondary and tertiary structure is encoded in the representations and can be identified by linear projections. Representation learning produces features that generalize across a range of applications, enabling state-of-the-art supervised prediction of mutational effect and secondary structure, and improving state-of-the-art features for long-range contact prediction.

synthetic biology↗

bioRxiv2019

The size of the immune repertoire of bacteria

Some bacteria and archaea possess an immune system, based on the CRISPR-Cas mechanism, that confers adaptive immunity against phage. In such species, individual bacteria maintain a "cassette" of viral DNA elements called spacers as a memory of past infections. The typical cassette contains a few dozen spacers. Given that bacteria can have very large genomes, and since having more spacers should confer a better memory, it is puzzling that so little genetic space would be devoted by bacteria to their adaptive immune system. Here, we identify a fundamental trade-off between the size of the bacterial immune repertoire and effectiveness of response to a given threat, and show how this tradeoff imposes a limit on the optimal size of the CRISPR cassette.

biophysics↗

bioRxiv2018

Oscillatory cortical forces promote three dimensional cell intercalations that shape the mandibular arch

Multiple vertebrate embryonic structures such as organ primordia are composed of a volume of confluent cells. Although mechanisms that shape tissue sheets are increasingly understood, those which shape a volume of cells remain obscure. Here we show 3D mesenchymal cell intercalations, rather than cell divisions and biophysical tissue properties, are essential to shape the mandibular arch of the mouse embryo. Using a genetically encoded vinculin tension sensor, we show that cortical force oscillations promote these intercalations. Genetic loss and gain of function approaches show that Wnt5a functions as a spatial cue to coordinate cell polarity with cytoskeletal oscillation. YAP/TAZ and PIEZO1 serve as downstream effectors of Wnt5a-mediated actomyosin bias and cytosolic calcium transients, respectively, to ensure appropriate tissue form during growth. Our data support oriented 3D cell neighbour exchange as a conserved mechanism driving volumetric morphogenesis.

developmental biology↗

bioRxiv2017

Bioty: A cloud-based development toolkit for programming experiments and interactive applications with living cells

Recent advancements in life-science instrumentation and automation enable entirely new modes of human interaction with microbiological processes and corresponding applications for science and education through biology cloud labs. A critical barrier for remote life-science experimentation is the absence of suitable abstractions and interfaces for programming living matter. To this end we conceptualize a programming paradigm that provides stimulus control functions and sensor control functions for realtime manipulation of biological (physical) matter. Additionally, a simulation mode facilitates higher user throughput, program debugging, and biophysical modeling. To evaluate this paradigm, we implemented a JavaScript-based web toolkit, Bioty, that supports realtime interaction with swarms of phototactic Euglena cells hosted on a cloud lab. Studies with remote users demonstrate that individuals with little to no biology knowledge and intermediate programming knowledge were able to successfully create and use scientific applications and games. This work informs the design of programming environments for controlling living matter in general and lowers the access barriers to biology experimentation for professional and citizen scientists, learners, and the lay public.\n\nSignificance StatementBiology cloud labs are an emerging approach to lower access barriers to life-science experimentation. However, suitable programming approaches and user interfaces are lacking, especially ones that enable the interaction with the living matter itself - not just the control of equipment. Here we present and implement a corresponding programming paradigm for realtime interactive applications with remotely housed biological systems, and which is accessible and useful for scientists, programmers and lay people alike. Our user studies show that scientists and non-scientists are able to rapidly develop a variety of applications, such as interactive biophysics experiments and games. This paradigm has the potential to make first-hand experiences with biology accessible to all of society and to accelerate the rate of scientific discovery.

bioengineering↗

bioRxiv2017

NMDA-receptor antibodies alter cortical microcircuit dynamics

NMDA-receptor antibodies (NMDAR-Ab) cause an autoimmune encephalitis with a diverse range of electroencephalographic (EEG) abnormalities. NMDAR-Ab are believed to disrupt receptor function, but how blocking this excitatory neurotransmitter can lead to paroxysmal EEG abnormalities - or even seizures - is poorly understood. Here, we show that NMDAR-Ab change intrinsic cortical connections and neuronal population dynamics to alter the spectral composition of spontaneous EEG activity, and predispose to paroxysmal EEG abnormalities. Based on local field potential recordings in a mouse model, we first validate a dynamic causal model of NMDAR-Ab effects on cortical microcircuitry. Using this model, we then identify the key synaptic parameters that best explain EEG paroxysms in paediatric patients with NMDAR-Ab encephalitis. Finally, we use the mouse model to show that NMDAR-Ab- related changes render microcircuitry critically susceptible to overt EEG paroxysms, when these key parameters are changed. These findings offer mechanistic insights into circuit-level dysfunction induced by NMDAR-Ab.

neuroscience↗