V.A.P. (Vitor) Martins dos Santos

Draft Genome Sequence of the Oleaginous Green Alga Tetradesmus obliquus UTEX 393

ABSTRACT The microalgae Tetradesmus obliquus is able to maintain a high photosynthetic efficiency under nitrogen limitation and is considered a promising green microalgae for sustainable production of diverse compounds, including biofuels. Here, we report the first draft whole-genome shotgun sequencing of T. obliquus. The final assembly comprises 108,715,903 bp with over 1,368 scaffolds.

Necrotizing soft tissue infections – a multicentre, prospective observational study (INFECT): protocol and statistical analysis plan

The INFECT project aims to advance our understanding of the pathophysiological mechanisms in necrotizing soft tissue infections (NSTIs). The INFECT observational study is part of the INFECT project with the aim of studying the clinical profile of patients with NSTIs and correlating these to patient‐important outcomes. With this protocol and statistical analysis plan we describe the methods used to obtain data and the details of the planned analyses.

Systems biology at work.

In his editorial overview for the 2008 Special Issue on this topic, the late Jaroslav Stark pointedly noted that systems biology is no longer a niche pursuit, but a recognized discipline in its own right “noisily” coming of age [1]. Whilst general underlying principles and basic techniques are now reasonably well established, we see a progressive shift from “fishing expeditions” through seas of “omics” data towards increasingly more model-driven research generating verifiable hypotheses that are iteratively tested and refined across different aggregation levels. In this special issue, we illustrate this ethos of systems biology at work in various fields through an eclectic series of articles thematically grouped under “methods and tools in network analysis”, “emerging and enabling technologies”, “microbes in disease and the environment”, “human health and disease” and “synthetic biology”.

Combining Genetic Circuit and Microbial Growth Kinetic Models: A Challenge for Biological Modelling

Abstract A modelling framework that consists of model building, validation and analysis, leading to model-based design of experiments and to the application of optimisation-based model-predictive control strategies for the development of optimised bioprocesses is presented. An example of this framework is given with the construction and experimental validation of a dynamic mathematical model of the Ps/Pr promoters system of the TOL plasmid, which is used for the metabolism of m -xylene by Pseudomonas putida mt-2. Furthermore, the genetic circuit model is combined with the growth kinetics of the strain in batch cultures, demonstrating how the description of key genetic circuits can facilitate the improvement of existing growth kinetic models that fail to predict unusual growth patterns. Consequently, the dynamic model is combined with global sensitivity analysis, which is used to identify the presence of significant model parameters, constituting a model-based methodology for the formulation of genetic circuit optimization methods.

Synthetic Biology in Health and Disease

Synthetic biology draws on the understanding from genetics, biology, chemistry, physics, engineering, and computational sciences to (re-)design and (re-)engineer biological functions. Here we address how synthetic biology can be possibly deployed to promote health and tackle disease. We discuss how drugs can be produced in more affordable ways, how new medicines can be developed, how the re-design of cellular pathways can correct endogenous malfunctioning in a series of diseases, how bacteria can be engineered to kill tumors, and how bacterial communities in the intestine can be modulated to restore gut homeostasis and prevent metabolic diseases. We indicate how new biomedical materials can be synthetized to replace tissues, how new biosensors can assist in diagnosis and prognosis, and how synthetic biology can help preventing the onset of disease in those cases in which until now only diagnosis was possible. On the basis of this, we discuss towards what directions synthetic biology in health and disease may develop in the future.

Predicting microbial growth kinetics with the use of genetic circuit models

Abstract A novel modeling approach for the description of bioprocesses is proposed, linking microbial growth kinetics to gene regulation. An example is given with the development and experimental validation of a dynamic mathematical model of the TOL plasmid of Pseudomonas putida mt-2, which is used for the metabolism of m-xylene. The model of this genetic circuit is coupled to a growth kinetic model through predictions of rate-limiting enzyme concentrations that control biomass growth and substrate consumption. Batch cultures of mt-2 fed with m-xylene were performed to estimate model parameters and to confirm that the combined model successfully describes the bioprocess, through mRNA, biomass and m-xylene concentration measurements. However, mathematical models developed exclusively based on macroscopic measurements failed to predict the process variables, highlighting the importance of gene regulation for the development of advanced biological models.