Measuring single-cell gene expression dynamics in bacteria using fluorescence time-lapse microscopy

Quantitative single-cell time-lapse microscopy is a powerful method for analyzing gene circuit dynamics and heterogeneous cell behavior. We describe the application of this method to imaging bacteria by using an automated microscopy system. This protocol has been used to analyze sporulation and competence differentiation in Bacillus subtilis, and to quantify gene regulation and its fluctuations in individual Escherichia coli cells. The protocol involves seeding and growing bacteria on small agarose pads and imaging the resulting microcolonies. Images are then reviewed and analyzed using our laboratory's custom MATLAB analysis code, which segments and tracks cells in a frame-to-frame method. This process yields quantitative expression data on cell lineages, which can illustrate dynamic expression profiles and facilitate mathematical models of gene circuits. With fast-growing bacteria, such as E. coli or B. subtilis, image acquisition can be completed in 1 d, with an additional 1-2 d for progressing through the analysis procedure.     

Direct inhibition of myosin II effectively blocks glioma invasion in the presence of multiple motogens

Anaplastic gliomas, the most common and malignant of primary brain tumors, frequently contain activating mutations and amplifications in promigratory signal transduction pathways. However, targeting these pathways with individual signal transduction inhibitors does not appreciably reduce tumor invasion, because these pathways are redundant; blockade of any one pathway can be overcome by stimulation of another. This implies that a more effective approach would be to target a component at which these pathways converge. In this study, we have investigated whether the molecular motor myosin II represents such a target by examining glioma invasion in a series of increasingly complex models that are sensitive to platelet-derived growth factor, epidermal growth factor, or both. Our results lead to two conclusions. First, malignant glioma cells are stimulated to invade brain through the activation of multiple signaling cascades not accounted for in simple in vitro assays. Second, even though there is a high degree of redundancy in promigratory signaling cascades in gliomas, blocking tumor invasion by directly targeting myosin II remains effective. Our results thus support our hypothesis that myosin II represents a point of convergence for signal transduction pathways that drive glioma invasion and that its inhibition cannot be overcome by other motility mechanisms.     

The Akt-SRPK-SR Axis Constitutes a Major Pathway in Transducing EGF Signaling to Regulate Alternative Splicing in the Nucleus

Pre-mRNA splicing is regulated by developmental and environmental cues, but little is known about how specific signals are transduced in mammalian cells to regulate this critical gene expression step. Here, we report massive reprogramming of alternative splicing in response to EGF signaling. By blocking individual branches in EGF signaling, we found that Akt activation plays a major role, while other branches, such as the JAK/STAT and ERK pathways, make minor contributions to EGF-induced splicing. Activated Akt next branches to SR protein-specific kinases, rather than mTOR, by inducing SRPK autophosphorylation that switches the splicing kinases from Hsp70- to Hsp90-containing complexes. This leads to enhanced SRPK nuclear translocation and SR protein phosphorylation. These findings reveal a major signal transduction pathway for regulated splicing and place SRPKs in a central position in the pathway, consistent with their reputed roles in a large number of human cancers.     

Successes,failures, and opportunities in the practical application of drift-foraging models

Accurately measuring productive capacity in streams is challenging, and field methods have generally focused on the limiting role of physical habitat attributes (e.g. channel gradient, depth, velocity, substrate). Because drift-foraging models uniquely integrate the effects of both physical habitat (velocity and depth) and prey abundance (invertebrate drift) on energy intake for drift-feeding fishes, they provide a coherent and transferable framework for modelling individual growth that includes the effects of both physical habitat and biological production. Despite this, drift-foraging models have been slow to realize their potential in an applied context. Practical applications have been hampered by difficulties in predicting growth (rather than habitat choice), and scaling predictions of individual growth to reach scale habitat capacity, which requires modelling the partitioning of resources among individuals and depletion of drift through predation. There has also been a general failure of stream ecologists to adequately characterize spatial and temporal variation in invertebrate drift within and among streams, so that sources of variation in this key component of drift-foraging models remain poorly understood. Validation of predictions of habitat capacity have been patchy or lacking, until recent studies demonstrating strong relationships between drift flux, modeled Net Energy Intake, and fish biomass. Further advances in the practical application of drift-foraging models will require i) a better understanding of the factors that cause variation in drift, better approaches for modelling drift, and more standardized methods for characterizing it; ii) identification of simple diagnostic metrics that correlate strongly with more precise but time-consuming bioenergetic assessments of habitat quality; and iii) a better understanding of how variation in drift-foraging strategies are associated with other suites of co-evolved traits that ecologically differentiate taxa of drift-feeding salmonids.     

Covasim: An agent-based model of COVID-19 dynamics and interventions

The COVID-19 pandemic has created an urgent need for models that can project epidemic trends, explore intervention scenarios, and estimate resource needs. Here we describe the methodology of Covasim (COVID-19 Agent-based Simulator), an open-source model developed to help address these questions. Covasim includes country-specific demographic information on age structure and population size; realistic transmission networks in different social layers, including households, schools, workplaces, long-term care facilities, and communities; age-specific disease outcomes; and intrahost viral dynamics, including viral-load-based transmissibility. Covasim also supports an extensive set of interventions, including non-pharmaceutical interventions, such as physical distancing and protective equipment; pharmaceutical interventions, including vaccination; and testing interventions, such as symptomatic and asymptomatic testing, isolation, contact tracing, and quarantine. These interventions can incorporate the effects of delays, loss-to-follow-up, micro-targeting, and other factors. Implemented in pure Python, Covasim has been designed with equal emphasis on performance, ease of use, and flexibility: realistic and highly customized scenarios can be run on a standard laptop in under a minute. In collaboration with local health agencies and policymakers, Covasim has already been applied to examine epidemic dynamics and inform policy decisions in more than a dozen countries in Africa, Asia-Pacific, Europe, and North America.     

High yield of biologically active recombinant human amelogenin using the baculovirus expression system

The amelogenins are secreted by the ameloblast cells of developing teeth; they constitute about 90% of the enamel matrix proteins and play an important role in enamel biomineralization. Recent evidence suggests that amelogenin may also be involved in the regeneration of the periodontal tissues and that different isoforms may have cell-signalling effects. During enamel development and mineralization, the amelogenins are lost from the tissue due to sequential degradation by specific proteases, making isolation of substantial purified quantities of full-length amelogenin challenging. The aim of the present study was to express and characterize a recombinant human amelogenin protein in the eukaryotic baculovirus system in quantities sufficient for structural and functional studies. Human cDNA coding for a 175 amino acid amelogenin protein was subcloned into the pFastBac HTb vector (Invitrogen), this system adds a hexa-histidine tag and an rTEV protease cleavage site to the amino terminus of the expressed protein, enabling effective one-step purification by Ni2+-NTA affinity chromatography. The recombinant protein was expressed in Spodoptera frugiperda (Sf9) insect cells and the yield of purified his-tagged human amelogenin (rHAM+) was up to 10 mg/L culture. Recombinant human amelogenin (rHAM+) was characterized by SDS-PAGE, Western blot, ESI-TOF spectrometry, peptide mapping, and MS/MS sequencing. Production of significant amounts of pure, full-length amelogenin opened up the possibility to investigate novel functions of amelogenin. Our recent in vivo regeneration studies reveal that the rHAM+ alone could bring about regeneration of the periodontal tissues; cementum, periodontal ligament, and bone.     

Clinical characterization of individuals with deletions of genes in holoprosencephaly pathways by aCGH refines the phenotypic spectrum of HPE

Holoprosencephaly (HPE) is the most common developmental forebrain anomaly in humans. Both environmental and genetic factors have been identified to play a role in the HPE phenotype. Previous studies of the genetic bases of HPE have taken a phenotype-first approach by examining groups of patients with HPE for specific mutations or deletions in known or candidate HPE genes. In this study, we characterized the presence or absence of HPE or a microform in 136 individuals in which microarray-based comparative genomic hybridization (aCGH) identified a deletion of one of 35 HPE loci. Frank holoprosencephaly was present in 11 individuals with deletions of one of the common HPE genes SHH, ZIC2, SIX3, and TGIF1, in one individual with a deletion of the HPE8 locus at 14q13, and in one individual with a deletion of FGF8, whereas deletions of other HPE loci and candidate genes (FOXA2 and LRP2) expressed microforms of HPE. Although individuals with deletions of other HPE candidates (DISP1, LSS, HHIP, SMO, BMP4, CDON, CDC42, ACVR2A, OTX2, and WIF1) had clinically significant features, none had frank HPE or a microform. A search for significant aCGH findings in individuals referred for testing for HPE revealed a novel association of a duplication involving GSK3B at 3q13.33 with HPE or a microform, seen in two unrelated individuals.     

Determining protein loop conformation using scaling-relaxation techniques.

We recently developed a rapid loop closure algorithm in which bond lengths are scaled to constrain the ends of a segment to match a known distance and then gradually relaxed to their standard values, with boundary constraints maintained. Although the algorithm predicted the Zif286 zinc-finger loop to within approximately 2 A, it had a serious limitation that made its more general use tentative: it omitted the atomic environment of the loop. Here we report an extension of the algorithm to take into account the protein environment surrounding a given loop from the outset of the conformational search and show that it predicts structure with an efficiency and accuracy that could not be achieved without continuous environmental inclusion. The algorithm should be widely applicable to structure determination when complete experimental information is unavailable.