The cytoplasm of living cells: A functional mixture of thousands of components

Inside every living cell is the cytoplasm: a fluid mixture of thousands of different macromolecules, predominantly proteins. This mixture is where most of the biochemistry occurs that enables living cells to function, and it is perhaps the most complex liquid on earth. Here we take an inventory of what is actually in this mixture. Recent genome-sequencing work has given us for the first time at least some information on all of these thousands of components. Having done so we consider two physical phenomena in the cytoplasm: diffusion and possible phase separation. Diffusion is slower in the highly crowded cytoplasm than in dilute solution. Reasonable estimates of this slowdown can be obtained and their consequences explored, for example, monomer-dimer equilibria are established approximately twenty times slower than in a dilute solution. Phase separation in all except exceptional cells appears not to be a problem, despite the high density and so strong protein-protein interactions present. We suggest that this may be partially a byproduct of the evolution of other properties, and partially a result of the huge number of components present.Comment: 11 pages, 1 figure, 1 tabl

Evolution of protein interfaces in multimers and fibrils

A majority of cellular proteins function as part of multimeric complexes of two or more subunits. Multimer formation requires interactions between protein surfaces that lead to closed structures, such as dimers and tetramers. If proteins interact in an open-ended way, uncontrolled growth of fibrils can occur, which is likely to be detrimental in most cases. We present a statistical physics model that allows aggregation of proteins as either closed dimers or open fibrils of all lengths. We use pairwise amino-acid contact energies to calculate the energies of interacting protein surfaces. The probabilities of all possible aggregate configurations can be calculated for any given sequence of surface amino acids. We link the statistical physics model to a population genetics model that describes the evolution of the surface residues. When proteins evolve neutrally, without selection for or against multimer formation, we find that a majority of proteins remain as monomers at moderate concentrations, but strong dimer-forming or fibril-forming sequences are also possible. If selection is applied in favor of dimers or in favor of fibrils, then it is easy to select either dimer-forming or fibril-forming sequences. It is also possible to select for oriented fibrils with protein subunits all aligned in the same direction. We measure the propensities of amino acids to occur at interfaces relative to noninteracting surfaces and show that the propensities in our model are strongly correlated with those that have been measured in real protein structures. We also show that there are significant differences between amino acid frequencies at isologous and heterologous interfaces in our model, and we observe that similar effects occur in real protein structures

Turing Instability in a Boundary-fed System

The formation of localized structures in the chlorine dioxide-idodine-malonic acid (CDIMA) reaction-diffusion system is investigated numerically using a realistic model of this system. We analyze the one-dimensional patterns formed along the gradients imposed by boundary feeds, and study their linear stability to symmetry-breaking perturbations (Turing instability) in the plane transverse to these gradients. We establish that an often-invoked simple local linear analysis which neglects longitudinal diffusion is inappropriate for predicting the linear stability of these patterns. Using a fully nonuniform analysis, we investigate the structure of the patterns formed along the gradients and their stability to transverse Turing pattern formation as a function of the values of two control parameters: the malonic acid feed concentration and the size of the reactor in the dimension along the gradients. The results from this investigation are compared with existing experiments.Comment: 41 pages, 18 figures, to be published in Physical Review

Gravitational clustering of relic neutrinos and implications for their detection

We study the gravitational clustering of big bang relic neutrinos onto existing cold dark matter (CDM) and baryonic structures within the flat $\Lambda$CDM model, using both numerical simulations and a semi-analytical linear technique, with the aim of understanding the neutrinos' clustering properties for direct detection purposes. In a comparative analysis, we find that the linear technique systematically underestimates the amount of clustering for a wide range of CDM halo and neutrino masses. This invalidates earlier claims of the technique's applicability. We then compute the exact phase space distribution of relic neutrinos in our neighbourhood at Earth, and estimate the large scale neutrino density contrasts within the local Greisen--Zatsepin--Kuzmin zone. With these findings, we discuss the implications of gravitational neutrino clustering for scattering-based detection methods, ranging from flux detection via Cavendish-type torsion balances, to target detection using accelerator beams and cosmic rays. For emission spectroscopy via resonant annihilation of extremely energetic cosmic neutrinos on the relic neutrino background, we give new estimates for the expected enhancement in the event rates in the direction of the Virgo cluster.Comment: 38 pages, 8 embedded figures, iopart.cls; v2: references added, minor changes in text, to appear in JCA

Overview of mathematical approaches used to model bacterial chemotaxis II: bacterial populations

We review the application of mathematical modeling to understanding the behavior of populations of chemotactic bacteria. The application of continuum mathematical models, in particular generalized Keller–Segel models, is discussed along with attempts to incorporate the microscale (individual) behavior on the macroscale, modeling the interaction between different species of bacteria, the interaction of bacteria with their environment, and methods used to obtain experimentally verified parameter values. We allude briefly to the role of modeling pattern formation in understanding collective behavior within bacterial populations. Various aspects of each model are discussed and areas for possible future research are postulated

Cohort profile: the British Columbia COVID-19 Cohort (BCC19C)—a dynamic, linked population-based cohort

PurposeThe British Columbia COVID-19 Cohort (BCC19C) was developed from an innovative, dynamic surveillance platform and is accessed/analyzed through a cloud-based environment. The platform integrates recently developed provincial COVID-19 datasets (refreshed daily) with existing administrative holdings and provincial registries (refreshed weekly/monthly). The platform/cohort were established to inform the COVID-19 response in near “real-time” and to answer more in-depth epidemiologic questions.ParticipantsThe surveillance platform facilitates the creation of large, up-to-date analytic cohorts of people accessing COVID-19 related services and their linked medical histories. The program of work focused on creating/analyzing these cohorts is referred to as the BCC19C. The administrative/registry datasets integrated within the platform are not specific to COVID-19 and allow for selection of “control” individuals who have not accessed COVID-19 services.Findings to dateThe platform has vastly broadened the range of COVID-19 analyses possible, and outputs from BCC19C analyses have been used to create dashboards, support routine reporting and contribute to the peer-reviewed literature. Published manuscripts (total of 15 as of July, 2023) have appeared in high-profile publications, generated significant media attention and informed policy and programming. In this paper, we conducted an analysis to identify sociodemographic and health characteristics associated with receiving SARS-CoV-2 laboratory testing, testing positive, and being fully vaccinated. Other published analyses have compared the relative clinical severity of different variants of concern; quantified the high “real-world” effectiveness of vaccines in addition to the higher risk of myocarditis among younger males following a 2nd dose of an mRNA vaccine; developed and validated an algorithm for identifying long-COVID patients in administrative data; identified a higher rate of diabetes and healthcare utilization among people with long-COVID; and measured the impact of the pandemic on mental health, among other analyses.Future plansWhile the global COVID-19 health emergency has ended, our program of work remains robust. We plan to integrate additional datasets into the surveillance platform to further improve and expand covariate measurement and scope of analyses. Our analyses continue to focus on retrospective studies of various aspects of the COVID-19 pandemic, as well as prospective assessment of post-acute COVID-19 conditions and other impacts of the pandemic

Differential gene expression between squamous cell carcinoma of esophageus and its normal epithelium; altered pattern of mal, akr1c2, and rab11a expression

AIM: To identify the altered gene expression patterns in squamous cell carcinoma of esophagus (ESCC) in relation to adjacent normal esophageal epithelium. METHODS: Total RNA was extracted using SV total RNA isolation kit from snap frozen tissues of ESCC samples and normal esophageal epithelium far from the tumor. Radio-labeled cDNA were synthesized from equal quantities of total RNAs of tumor and normal tissues using combinations of 24 arbitrary 13-mer primers and three different anchoring oligo-dT primers and separated on sequencing gels. cDNA with considerable different amounts of signals in tumor and normal tissue were reamplified and cloned. Using southern blot, the clones of each band were controlled for false positive results caused by probable heterogeneity of cDNA population with the same size. Clones that confirmed differential expression by slot blot selected for sequencing and northern analysis. Corresponding full-length gene sequences was predicted using human genome project data, related transcripts were translated and used for various protein/motif searches to speculate their probable functions. RESULTS: The 97 genes showed different levels of cDNA in tumor and normal tissues of esophagus. The expression of mal gene was remarkably down regulated in all 10 surveyed tumor tissues. Akr1c2, a member of the aldo-keto reductase 1C family, which is involved in metabolism of sex hormones and xenobiotics, was up-regulated in 8 out of 10 inspected ESCC samples. Rab11a, RPL7, and RPL28 showed moderate levels of differential expression. Many other cDNAs remained to further studies. CONCLUSION: The mal gene which is switched-off in all ESCC samples can be considered as a tumor suppressor gene that more studies in its regulation may lead to valuable explanations in ESCC development. Akr1c2 which is up-regulated in ESCC probably plays an important role in tumor development of esophagus and may be proposed as a potential molecular target in ESCC treatments. Differential display technique in spite of many disadvantages is still a valuable technique in gene function exploration studies to find new candidates for improved ones like gene chips

A nutrient uptake role for bacterial cell envelope extensions

Bacteria exist in a variety of morphologies, but the relationship between cellular forms and biological functions remains poorly understood. We show that stalks (prosthecae), cylindrical extensions of the Caulobacter crescentus cell envelope, can take up and hydrolyze organic phosphate molecules and contain the high-affinity phosphate-binding protein PstS, but not PstA, a protein that is required for transport of phosphate into the cytoplasm. Therefore, uptake, hydrolysis, and periplasmic binding of a phosphate source can take place in the stalk, but high-affinity import must take place in the cell body. Furthermore, by using analytical modeling, we illustrate the biophysical advantage of the stalk as a morphological adaptation to the diffusion-limited, oligotrophic environments where C. crescentus thrives. This advantage is due to the fact that a stalk is long and thin, a favorable shape for maximizing contact with diffusing nutrients while minimizing increases in both surface area and cell volume