Biology subjects

Prakash, M.

Publications and source records attributed to Prakash, M..

7 recordsLinked to original sources

bioRxiv2018

Collective intercellular communication through ultra-fast hydrodynamic trigger waves

The biophysical relationships between sensors and actuators [1-5] have been fundamental to the development of complex life forms; Abundant flows are generated and persist in aquatic environments by swimming organisms [6-13], while responding promptly to external stimuli is key to survival [14-19]. Here, akin to a chain reaction [20-22], we present the discovery of hydrodynamic trigger waves in cellular communities of the protist Spirostomum ambiguum, propagating hundreds of times faster than the swimming speed. Coiling its cytoskeleton, Spirostomum can contract its long body by 50% within milliseconds [23], with accelerations reaching 14g-forces. Surprisingly, a single cellular contraction (transmitter) is shown to generate long-ranged vortex flows at intermediate Reynolds numbers, which can trigger neighbouring cells, in turn. To measure the sensitivity to hydrodynamic signals (receiver), we further present a high-throughput suction-flow device to probe mechanosensitive ion channel gating [24] by back-calculating the microscopic forces on the cell membrane. These ultra-fast hydrodynamic trigger waves are analysed and modelled quantitatively in a universal framework of antenna and percolation theory [25, 26]. A phase transition is revealed, requiring a critical colony density to sustain collective communication. Our results suggest that this signalling could help organise cohabiting communities over large distances, influencing long-term behaviour through gene expression, comparable to quorum sensing [16]. More immediately, as contractions release toxins [27], synchronised discharges could also facilitate the repulsion of large predators, or conversely immobilise large prey. We postulate that beyond protists numerous other freshwater and marine organisms could coordinate with variations of hydrodynamic trigger waves.

biophysics↗

bioRxiv2018

Coupled active systems encode emergent behavioral dynamics of the unicellular predator Lacrymaria olor

Multiple active systems in a cell work together to produce sophisticated cellular behaviors such as motility and search. However, it is often unclear how this coupling specifies the complex emergent dynamics that define such behaviors. As a model system, we analyzed the hunting strategy of Lacrymaria olor, a unicellular predatory ciliate that uses extreme morphological changes to extend, contract and whip an apparent \"cell neck\" over many body lengths to capture prey. Tracking millions of unique subcellular morphologies over time revealed that these fast dynamics encode a comprehensive local search behavior apparent only at longer timescales. This hunting behavior emerges as a tug-of-war between active sub-cellular structures that use surface cilia and cortex contractility to deform the structure of the neck. The resulting search space can be described mathematically using a small number of normal shape modes that change amplitude rapidly during hunts. The distribution of these shape modes in space and time reveals a transition point between tense and compressed neck morphologies at the mean neck length, such that new shapes are readily sampled by repeatedly extending and retracting across this critical length. Molecular perturbations to the cell-signaling controller show that coupling between ciliary and contractile programs is needed to maintain this length/shape relationship; neither system alone provides the dynamic repertoire of shapes necessary for comprehensive search. Our results highlight the utility of coupling antagonistic active systems as a strategy for encoding or engineering complex behaviors in molecular machines.\n\nOne Sentence Summary: Analysis of millions of unique cellular morphologies of the highly dynamic single-celled predator Lacrymaria olor reveals that it programs a comprehensive search space and emergent hunting behavior through coupling surface based active cilia and cortex based contractile molecular systems together.

systems biology↗

bioRxiv2018

Ultra-fast cellular contractions in the epithelium of T. adhaerens and the "active cohesion" hypothesis

By definition of multi-cellularity, all animals need to keep their cells attached and intact, despite internal and external forces. Cohesion between epithelial cells provides this key feature. In order to better understand fundamental limits of this cohesion, we study the epithelium mechanics of an ultra-thin (~25 um) primitive marine animal Trichoplax adhaerens, composed essentially of two flat epithelial layers. With no known extra-cellular-matrix and no nerves or muscles, T. adhaerens was claimed the \"simplest known living animal\", yet is still capable of coordinated locomotion and behavior. Here we report the discovery of the fastest epithelial cellular contractions to date to be found in T. adhaerens dorsal epithelium (50% shrinkage of apical cell area within one second, at least an order of magnitude faster than known examples). Live imaging reveals emergent contractile patterns that are mostly sporadic single-cell events, but also include propagating contraction waves across the tissue. We show that cell contraction speed can be explained by current models of non-muscle actin-myosin bundles without load, while the tissue architecture and unique mechanical properties are softening the tissue, minimizing the load on a contracting cell. We propose a hypothesis, in which the physiological role of the contraction dynamics is to avoid tissue rupture (\"active cohesion\"), a novel concept that can be further applied to engineering of active materials.\n\nOne Sentence SummaryWe report the fastest epithelial cell contractions known to date, show they fit the kinematics arising from current cytoskeletal models, and suggest the extreme tissue dynamics is a means to actively avoid rupture.

biophysics↗

bioRxiv2017

Using Mobile Phones As Acoustic Sensors For High-Throughput Surveillance Of Mosquito Ecology

The direct monitoring of mosquito populations in field settings is a crucial input for shaping appropriate and timely control measures for mosquito-borne diseases. Here, we demonstrate that commercially available mobile phones are a powerful tool for acoustically mapping mosquito species distributions worldwide. We show that even low-cost mobile phones with very basic functionality are capable of sensitively acquiring acoustic data on species-specific mosquito wingbeat sounds, while simultaneously recording the time and location of the human-mosquito encounter. We survey a wide range of medically important mosquito species, to quantitatively demonstrate how acoustic recordings supported by spatio-temporal metadata enable rapid, non-invasive species identification. As proof-of-concept, we carry out field demonstrations where minimally-trained users map local mosquitoes using their personal phones. Thus, we establish a new paradigm for mosquito surveillance that takes advantage of the existing global mobile network infrastructure, to enable continuous and large-scale data acquisition in resource-constrained areas.

ecology↗

bioRxiv2017

Mapping load-bearing in the mammalian spindle reveals local kinetochore-fiber anchorage that provides mechanical isolation and redundancy

Active forces generated at kinetochores move chromosomes, and the dynamic spindle must robustly anchor kinetochore-fibers (k-fibers) to bear this load. We know that the mammalian spindle body can bear the load of chromosome movement far from poles, but do not know where and how - physically and molecularly - this load is distributed across the spindle. In part, this is because perturbing and reading out spindle mechanics in live cells is difficult. Yet, answering this question is key to understanding how the spindle generates and responds to force, and performs its diverse mechanical functions. Here, we map load-bearing across the mammalian spindle in space-time, and dissect local anchorage mechanics and mechanism. To do so, we laser ablate single k-fibers at different spindle locations, and in different molecular backgrounds, and quantify at high time resolution the immediate relaxation of chromosomes, k-fibers, and microtubule speckles. We find that load redistribution is locally confined in all directions: along the first 3-4 m from kinetochores, scaling with k-fiber length, and laterally within ~2 m of k-fiber sides, without neighboring k-fibers sharing load. A phenomenological model constrains the mechanistic underpinnings of these data: it suggests that dense, transient crosslinks to the spindle along k-fibers bear the load of chromosome movement, but that these connections do not limit the timescale of spindle reorganization. The microtubule crosslinker NuMA is needed for the local load-bearing observed, while Eg5 and PRC1 are not, suggesting specialization in mechanical function and a novel function for NuMA throughout the spindle body. Together, the data and model suggest that widespread NuMA-mediated crosslinks locally bear load, providing mechanical isolation and redundancy while allowing spindle fluidity. These features are well-suited to support robust chromosome segregation.

cell biology↗

bioRxiv2017

Chemotaxis microsimulation: On the gain in nutrient uptake and bacterial cell division with chemotaxis mechanism

Bacterial swimming alternates between straight runs for several seconds and tumbles into random directions. Chemotactic bacteria remember nutrient sensing history, change tumble frequency to move toward nutrients. A question that has not been addressed is the significance of the nutrition gain and multiplication of bacterial population with chemotaxis mechanism. To quantify these effects, we introduce a microsimulation model, which seamlessly integrates detailed observations and assumptions about single bacterial tumbles, noisy sensing and nutrient uptake for studying up to a few millions of them in a population. We use the model to simulate absorption of nutrients from lysis and agar plates. Contrary to an intuitive feeling that chemotaxis could be useful under nutrient starvation, we see a significant effect only under nutrient rich conditions where bacteria with chemotaxis outgrow their non-chemotactic counterparts by hundreds of times. The model offers the flexibility to study the consequences of newer assumptions, and experimental conditions.\n\nAuthor SummaryChemotaxis is a mechanism that helps bacteria navigate towards nutrients. Several aspects of the mechanism have been well studied over the past 50 years. As most bacterial mechanisms are helpful evolutionarily to survive and to multiply, it would be a natural question to ask how much this swim helps bacteria to gain nutrition and consequently to multiply. However to our knowledge this question has not been asked. We develop a model that integrates bacterial motion, with sensing and nutrient uptake and show that only under nutrient rich conditions this mechanism helps.

biophysics↗

bioRxiv2016

Flowtrace: simple visualization of coherent structures in biological fluid flows

1We present a simple, intuitive algorithm for visualizing time-varying flow fields that can reveal complex flow structures with minimal user intervention. We apply this technique to a variety of biological systems, including the swimming currents of invertebrates and the collective motion of swarms of insects. We compare our results to more experimentally-diffcult and mathematically-sophisticated techniques for identifying patterns in fluid flows, and suggest that our tool represents an essential \"middle ground\" allowing experimentalists to easily determine whether a system exhibits interesting flow patterns and coherent structures without the need to resort to more intensive techniques. In addition to being informative, the visualizations generated by our tool are often striking and elegant, illustrating coherent structures directly from videos without the need for computational overlays. Our tool is available as fully-documented open-source code available for MATLAB, Python, or ImageJ at www.flowtrace.org.

biophysics↗