Neural Expectation Maximization

Many real world tasks such as reasoning and physical interaction require identification and manipulation of conceptual entities. A first step towards solving these tasks is the automated discovery of distributed symbol-like representations. In this paper, we explicitly formalize this problem as inference in a spatial mixture model where each component is parametrized by a neural network. Based on the Expectation Maximization framework we then derive a differentiable clustering method that simultaneously learns how to group and represent individual entities. We evaluate our method on the (sequential) perceptual grouping task and find that it is able to accurately recover the constituent objects. We demonstrate that the learned representations are useful for next-step prediction.Comment: Accepted to NIPS 201

Cheetah:a computational toolkit for cybergenetic control

Abstract Advances in microscopy, microfluidics, and optogenetics enable single-cell monitoring and environmental regulation and offer the means to control cellular phenotypes. The development of such systems is challenging and often results in bespoke setups that hinder reproducibility. To address this, we introduce Cheetah, a flexible computational toolkit that simplifies the integration of real-time microscopy analysis with algorithms for cellular control. Central to the platform is an image segmentation system based on the versatile U-Net convolutional neural network. This is supplemented with functionality to robustly count, characterize, and control cells over time. We demonstrate Cheetah’s core capabilities by analyzing long-term bacterial and mammalian cell growth and by dynamically controlling protein expression in mammalian cells. In all cases, Cheetah’s segmentation accuracy exceeds that of a commonly used thresholding-based method, allowing for more accurate control signals to be generated. Availability of this easy-to-use platform will make control engineering techniques more accessible and offer new ways to probe and manipulate living cells

A microfluidic platform for quantitative analysis of single mycobacteria cells

Thesis (Ph.D.)--Boston UniversityMycobacterium tuberculosis (MTB), the causative agent of tuberculosis (TB), is the leading bacterial cause of death worldwide. A significant barrier to global MTB eradication is 'latent' TB infection, where MTB persists in the human host in a metabolically dormant and highly drug-tolerant state. Latently infected individuals constitute a vast global reservoir of disease (~2 billion people worldwide), and the heightened drug tolerance of dormant MTB necessitates long antibiotic treatments (up to 9 months of combination antibiotic therapy). MTB dormancy is thought to be the result of an adaptive response to host-induced stresses, involving coordinated transcriptional regulation of hundreds of genes as well as numerous metabolic changes. Currently, our understanding of this process is limited by a lack of tools for studying dynamic behavior in single cells. Gene regulation is a dynamic phenomenon that occurs within each cell individually, but many assays rely on steady-state measurements of a population average and thus fail to capture important information about the dynamics of cellular behavior. Additionally, cell-to-cell phenotypic variation has been identified as a key source of microbial drug tolerance, further highlighting the need for single-cell studies. To address this need, we developed a microfluidic platform to study Mycobacteria species at the single-cell level. This platform enables on-chip culture and fluorescent imaging of live cells in precisely controlled conditions, and can thus be used to study dynamic processes within single cells as well as phenotypic heterogeneity across a cellular population. We used this platform to obtain diverse new insights about mycobacterial biology, using the fast-growing mycobacterium M smegmatis. 1) We directly observed gene regulation by the transcription factor KstR in single cells, confirming regulatory interactions that had been predicted computationally. 2)We analyzed morphology, growth, and division data across hundreds of single cells and found that cell division in Mycobacteria is governed using size-based, rather than time-based, control mechanisms. 3) We found that individual cells exhibit considerable differences in their responses to antibiotic stress, and that these differences have implications for cellular survival

Stiffness-Controlled Hydrogels for 3D Cell Culture Models

Nanofibrillated cellulose (NFC) hydrogel is a versatile biomaterial suitable, for example, for three-dimensional (3D) cell spheroid culturing, drug delivery, and wound treatment. By freeze-drying NFC hydrogel, highly porous NFC structures can be manufactured. We freeze-dried NFC hydrogel and subsequently reconstituted the samples into a variety of concentrations of NFC fibers, which resulted in different stiffness of the material, i.e., different mechanical cues. After the successful freeze-drying and reconstitution, we showed that freeze-dried NFC hydrogel can be used for one-step 3D cell spheroid culturing of primary mesenchymal stem/stromal cells, prostate cancer cells (PC3), and hepatocellular carcinoma cells (HepG2). No difference was observed in the viability or morphology between the 3D cell spheroids cultured in the freeze-dried and reconstituted NFC hydrogel and fresh NFC hydrogel. Furthermore, the 3D cultured spheroids showed stable metabolic activity and nearly 100% viability. Finally, we applied a convolutional neural network (CNN)-based automatic nuclei segmentation approach to automatically segment individual cells of 3D cultured PC3 and HepG2 spheroids. These results provide an application to culture 3D cell spheroids more readily with the NFC hydrogel and a step towards automatization of 3D cell culturing and analysis

Functional dissection of a gene expression oscillator in C. elegans

Gene expression oscillations control diverse biological processes. One such example of gene expression oscillations, are those found for thousands of genes during C. elegans larval development. However, it remains unclear whether and how gene expression oscillations regulate development processes in C. elegans. In this work, I aimed to study the molecular architecture and the system properties of the C. elegans oscillator to provide insight into potential developmental functions and reveal features that are unique, as well as those that are shared among oscillators. Here, performing temporally highly resolved mRNA-sequencing across all larval stages (L1-L4) of C. elegans development, we identified 3,739 genes, whose transcripts revealed high-amplitude oscillations (>2-fold from peak to trough), peaking once every larval stage with stable amplitudes, but variable periods. Oscillations appeared tightly coupled to the molts, but were absent from freshly hatched larvae, developmentally arrested dauer larvae and adults. Quantitative characterization of transitions between oscillatory and stable states of the oscillator showed that the stable states are similar to a particular phase of the oscillator, which coincided with molt exit. Given that these transitions are sensitive to food, we postulate that feeding might impact the state of the oscillator. These features appear rather unique, and hence a better understanding may help to reveal general principles of gene expression oscillators. Our RNAPII ChIP-seq revealed rhythmic occupancy of RNAPII at the promoters of oscillating genes, suggesting that mRNA transcript oscillations arise from rhythmic transcription. Given that oscillations are coupled to the repetitive molts and that the molecular mechanisms that regulate molting are unknown, we aimed to find transcription factors important for molting and oscillations. Hence, we screened 92 transcription factors that oscillate on the mRNA level for their role in molting and identified grh-1, myrf1, blmp-1, bed-3, nhr-23, nhr-25 and ztf-6. We showed that oscillatory activity of GRH-1 is required for timely completion of the molt, to prevent cuticle rupturing, and for oscillatory expression of structural components of the cuticle and ‘ECM regulators’, among others, including grh-1 itself. Hence, we propose GRH-1 as a putative component of the (sub-)oscillator that regulates molting. We showed that loss of BLMP-1 increased the duration of molts, affected cuticle integrity, and changed the oscillatory dynamics of a subset of genes in diverse ways. We postulate that BLMP-1 acts as factor that couples gene expression oscillations, and potentially sub-oscillators or repetitive developmental processes. In conclusion, this work provides insight into the function of the oscillator, and its system properties. Moreover, we identified relevant factors, which we propose as a starting point to unravel the molecular wiring of the C. elegans oscillator and its functional relevance

Hairy switches and oscillators - reconstructing the zebrafish segmentation clock

Formation of segments during vertebrate embryogenesis is regulated by a biological clock. Models and experimental data indicate that the core of this clock consists of a cell- autonomous single cell oscillator. This oscillator likely involves a genetic feedback loop of transcriptional repressors belonging to the hairy gene family. In zebrafish, three her genes, her1, hes6 and her7, have been identified as core oscillator components. The main purpose of this project was to study the molecular mechanism of the hairy gene negative feedback oscillator in single cells. To determine whether a single cell oscillator is part of the zebrafish segmentation clock, a cell dissociation protocol was established to track the expression of Her1 ex vivo. Upon dissociation, Her1 expression continued to oscillate for up to three cycles. The period of oscillations was significantly slower than that of the segmentation clock, but appears to speed up in the presence of serum. To test whether the hairy gene interactions are sufficient to generate oscillations in single cells, a protocol was established that uses synthetic biology principles to design, construct and characterize hairy gene networks in yeast. First a library of network parts, containing hairy genes, promoters and Her binding sites was generated and subsequently assembled into simple devices to test their functionality in yeast. The three core oscillator components, Her1, Hes6 and Her7, were characterized and optimized for expression in yeast. In the SWITCH-OFF assay, the Her1 protein, modified with a MigED yeast repressor domain, was found to function as a transcriptional repressor in yeast, while Hes6 with the same modification can not. The dissociation of segmentation clock cells provides the first direct evidence that single cell oscillators exist in zebrafish. In this system, oscillator dynamics can be studied without the interactions of higher level clock components. In parallel, establishing a yeast chassis for hairy gene networks provides a novel technique to directly test predicted oscillator mechanisms by constructing them ’bottom up’