Biology subjects

Curtis, T. P.

Publications and source records attributed to Curtis, T. P..

4 recordsLinked to original sources

bioRxiv2024

The probability and duration of immigration in microbial communities

Immigration is a fundamental feature of microbial communities. We propose a method to determine the probability (Pi) that a number of immigrants (i) can attain an abundance N using the ratio of the probabilities of death q and division or "birth" p and the gamblers ruin equation: Pi= (1-(q/p)i/(1-(q/p)N). We estimate the probability of successful bioaugmentation or transplantation, the fate of a mutation infection and extinction. For example, an inoculum of 108 bacteria with a q/p of 1.00000001 has a 10-43 chance of attaining an abundance of 1010. The immigration parameter used in neutral models, m is 1/(1-q/p). We calculated the long-term average value of m and q/p in a wastewater treatment plant. The value of m varies by >5 orders of magnitude, with a curious bimodal distribution. However, all the values of q/p are very close to, but greater than, 1. We expect the long-term average value of q/p to be [~]1 in all stable microbial communities. In the absence of migration, bacterial populations with a q/p [≥]1 will go extinct with probability 1. The link between q/p and infectious dose is known and we demonstrate that, in principle, the gamblers ruin equation can estimate the infectious dose in naturally occurring infections, using Vibrio cholerae "carriers" to illustrate the point. We use the ratio q/p to estimate the time (measured in events or solar time) for a given change in abundance to happen. When q/p=1, extinction in even a small microbial population will take thousands of years.

microbiology↗

bioRxiv2021

Looking for lipases and lipolytic organisms in low-temperature anaerobic reactors treating domestic wastewater

Poor lipid degradation limits low-temperature anaerobic treatment of domestic wastewater even when psychrophiles are used. We combined metagenomics and metaproteomics to find lipolytic bacteria and their potential, and actual, cold-adapted extracellular lipases in anaerobic membrane bioreactors treating domestic wastewater at 4{degrees}C and 15{degrees}C. Of the 40 recovered putative lipolytic metagenome-assembled genomes (MAGs), only three (Chlorobium, Desulfobacter, and Mycolicibacterium) were common and abundant (relative abundance [≥] 1%) in all reactors. Notably, some MAGs that represented aerobic autotrophs contained lipases. Therefore, we hypothesised that the lipases we found are not always associated with exogenous lipid degradation and can have other roles such as polyhydroxyalkanoates (PHA) accumulation/degradation and interference with the outer membranes of other bacteria. Metaproteomics did not provide sufficient proteome coverage for relatively lower abundant proteins such as lipases though the expression of fadL genes, long-chain fatty acid transporters, was confirmed for four genera (Dechloromonas, Azoarcus, Aeromonas and Sulfurimonas), none of which were recovered as putative lipolytic MAGs. Metaproteomics also confirmed the presence of 15 relatively abundant ([≥]1%) genera in all reactors, of which at least 6 can potentially accumulate lipid/polyhydroxyalkanoates. For most putative lipolytic MAGs, there was no statistically significant correlation between the read abundance and reactor conditions such as temperature, phase (biofilm and bulk liquid), and feed type (treated by ultraviolet light or not). Results obtained by metagenomics and metaproteomics did not confirm each other and further work is required to identify the true lipid degraders in these systems.

molecular biology↗

bioRxiv2021

Investigating the growth of an engineered strain of Cyanobacteria with an Agent-Based Model and a Recurrent Neural Network

A computational framework combining Agent-Based Models (ABMs) and Deep Learning techniques was developed to help design microbial communities that convert light and CO2 into useful bioproducts. An ABM that accounts for CO2, light, sucrose export rate and cell-to-cell mechanical interactions was used to investigate the growth of an engineered sucrose-exporting strain of Synechococcus elongatus PCC 7942. The ABM simulations produced population curves and synthetic images of colony growth. The curves and the images were analyzed, and growth was correlated to nutrients availability and colonies initial spatial distribution. To speed up the ABM simulations, a metamodel based on a Recurrent Neural Network, RNN, was trained on the synthetic images of growth. This metamodel successfully reproduced the population curves and the images of growth at a lower computational cost. The computational framework presented here paves the road towards designing microbial communities containing sucrose-exporting Synechococcus elongatus PCC 7942 by exploring the solution space in silico first.

microbiology↗

bioRxiv2019

NUFEB: A Massively Parallel Simulator for Individual-based Modelling of Microbial Communities

We present NUFEB, a flexible, efficient, and open source software for simulating the 3D dynamics of microbial communities. The tool is based on the Individual-based Modelling (IbM) approach, where microbes are represented as discrete units and their behaviour changes over time due to a variety of processes. This approach allows us to study population behaviours that emerge from the interaction between individuals and their environment. NUFEB is built on top of the classical molecular dynamics simulator LAMMPS, which we extended with IbM features. A wide range of biological, physical and chemical processes are implemented to explicitly model microbial systems. NUFEB is fully parallelised and allows for the simulation of large numbers of microbes (107 individuals and beyond). The parallelisation is based on a domain decomposition scheme that divides the domain into multiple sub-domains which are distributed to different processors. NUFEB also offers a collection of post-processing routines for the visualisation and analysis of simulation output. In this article, we give an overview of NUFEBs functionalities and implementation details. We provide examples that illustrate the type of microbial systems NUFEB can be used to model and simulate.\n\nAuthor summaryIndividual-based Models (IbM) are one of the most promising frameworks to study microbial communities, as they can explicitly describe the behaviour of each cell. The development of a general-purpose IbM solver should focus on efficiency and flexibility due to the unique characteristics of microbial systems. However, available tools for these purposes present significant limitations. Most of them only facilitate serial computing for single simulation, or only focus on biological processes, but do not model mechanical and chemical processes in detail. In this work, we introduce the IbM solver NUFEB that addresses these shortcoming. The tool facilitates the modelling of much needed biological, chemical, physical and individual microbes in detail, and offers the flexibility of model extension and customisation. NUFEB is also fully parallelised and allows for the simulation of large complex microbial system. In this paper, we first give an overview of NUFEBs functionalities and implementation details. Then, we use NUFEB to model and simulate a biofilm system with fluid dynamics, and a large and complex biofilm system with multiple microbial functional groups and multiple nutrients.\n\nThis is a PLOS Computational Biology Software paper.

microbiology↗