Uniform sampling of steady states in metabolic networks: heterogeneous scales and rounding

The uniform sampling of convex polytopes is an interesting computational problem with many applications in inference from linear constraints, but the performances of sampling algorithms can be affected by ill-conditioning. This is the case of inferring the feasible steady states in models of metabolic networks, since they can show heterogeneous time scales . In this work we focus on rounding procedures based on building an ellipsoid that closely matches the sampling space, that can be used to define an efficient hit-and-run (HR) Markov Chain Monte Carlo. In this way the uniformity of the sampling of the convex space of interest is rigorously guaranteed, at odds with non markovian methods. We analyze and compare three rounding methods in order to sample the feasible steady states of metabolic networks of three models of growing size up to genomic scale. The first is based on principal component analysis (PCA), the second on linear programming (LP) and finally we employ the lovasz ellipsoid method (LEM). Our results show that a rounding procedure is mandatory for the application of the HR in these inference problem and suggest that a combination of LEM or LP with a subsequent PCA perform the best. We finally compare the distributions of the HR with that of two heuristics based on the Artificially Centered hit-and-run (ACHR), gpSampler and optGpSampler. They show a good agreement with the results of the HR for the small network, while on genome scale models present inconsistencies.Comment: Replacement with major revision

Metabolic Complementation in Bacterial Communities: Necessary Conditions and Optimality

Bacterial communities may display metabolic complementation, in which different members of the association partially contribute to the same biosynthetic pathway. In this way, the end product of the pathway is synthesized by the community as a whole. However, the emergence and the benefits of such complementation are poorly understood. Herein, we present a simple model to analyze the metabolic interactions among bacteria, including the host in the case of endosymbiotic bacteria. The model considers two cell populations, with both cell types encoding for the same linear biosynthetic pathway. We have found that, for metabolic complementation to emerge as an optimal strategy, both product inhibition and large permeabilities are needed. In the light of these results, we then consider the patterns found in the case of tryptophan biosynthesis in the endosymbiont consortium hosted by the aphid Cinara cedri. Using in-silico computed physicochemical properties of metabolites of this and other biosynthetic pathways, we verified that the splitting point of the pathway corresponds to the most permeable intermediate.Financial support from Spanish Government (grant reference: BFU2012-39816-C02-01 co-financed by FEDER funds and Ministerio de Economía y Competitividad) and Generalitat Valenciana (grant reference: PROMETEOII/2014/065) is grateful acknowledged.Peer reviewe

Quantifying the benefit of a proteome reserve in fluctuating environments.

The overexpression of proteins is a major burden for fast-growing bacteria. Paradoxically, recent characterization of the proteome of Escherichia coli found many proteins expressed in excess of what appears to be optimal for exponential growth. Here, we quantitatively investigate the possibility that this overexpression constitutes a strategic reserve kept by starving cells to quickly meet demand upon sudden improvement in growth conditions. For cells exposed to repeated famine-and-feast cycles, we derive a simple relation between the duration of feast and the allocation of the ribosomal protein reserve to maximize the overall gain in biomass during the feast

Constrained Allocation Flux Balance Analysis

New experimental results on bacterial growth inspire a novel top-down approach to study cell metabolism, combining mass balance and proteomic constraints to extend and complement Flux Balance Analysis. We introduce here Constrained Allocation Flux Balance Analysis, CAFBA, in which the biosynthetic costs associated to growth are accounted for in an effective way through a single additional genome-wide constraint. Its roots lie in the experimentally observed pattern of proteome allocation for metabolic functions, allowing to bridge regulation and metabolism in a transparent way under the principle of growth-rate maximization. We provide a simple method to solve CAFBA efficiently and propose an "ensemble averaging" procedure to account for unknown protein costs. Applying this approach to modeling E. coli metabolism, we find that, as the growth rate increases, CAFBA solutions cross over from respiratory, growth-yield maximizing states (preferred at slow growth) to fermentative states with carbon overflow (preferred at fast growth). In addition, CAFBA allows for quantitatively accurate predictions on the rate of acetate excretion and growth yield based on only 3 parameters determined by empirical growth laws.Comment: 21 pages, 6 figures (main) + 33 pages, various figures and tables (supporting); for the supplementary MatLab code, see http://tinyurl.com/h763es

Deep Learning for Plant Phenotyping

Plant Phenotyping is an emerging science which provides us the knowledge to better understand plants. Indeed, the study of the link between genetic background and environment in which plants develop can help us to determine cures for plants’ sicknesses and new ways to improve yields using limited resources. In this regard, one of the main aspects of Plant Phenotyping that were studied in the past, was Root Phenotyping, which is based on the study of the root architectures. In particular, today with great technology innovations, it was possible to focus the research on non-invasive approaches which allow to study the root development belowground without altering the natural plants’ environment. One of the most common practices, is to make use of X-ray microcomputed tomography

The density of badger setts in a natural river corridor (NE Italy)

The European badger Meles meles (Linnaeus, 1758) is a common semifossorial mustelid species widely distributed throughout Europe. It also shows a high degree of plasticity, adapting its spatial and temporal behaviour to live in highly disturbed environments. Badgers live in social groups occupying underground systems called setts, which could be classified as “main” (i.e., the complex systems with a great number of entrances), and as “outliers”, “annexes” and “subsidiary” (i.e., the other burrows with a low number of entrances). An extensive scientific literature occurs on the ecology and biology of this species, and some information is available also for setts density in Europe and in Italy, too. However, since badgers may inhabit a wide variety of habitats, the setts density varies significantly both locally and on a large scale. We aimed to provide setts density in a river basin in the North-East of Italy. From January to March 2022, a sett survey was conducted in the eastern plain of Friuli Venezia Giulia Region (NE Italy), along the floodplains of the lowest reaches of Isonzo/Soca river basin, from Pavia di Udine (Torre river) to the Isonzo river mouth, a natural corridor surrounded by a highly human-modified matrix. Transects to collect setts information were made in the entire area of 27.82 km2 by two or three operators. For each sett, we recorded the geo-referenced location, the type (main, subsidiary and outliers), the habitat, and the number of entrances. To estimate the density, we only considered active main setts, dividing their number by the area. A total of 22 main setts were identified within the floodplains, corresponding to a density of 0.79 setts/km2. The mean number of entrances was 13.67 (min: 5, max: 28) and they were mainly recorded in forested patches (riverine forests and transitional woodlands-shrublands). We founded other 14 subsidiaries and 13 outliers setts. The density estimated in our study area is remarkably high compared to those estimated in similar environmental conditions (e.g., Po plain area, NW Italy), but considerably lower than those reported for natural habitats (e.g., Alpine area). Even if we did not specifically analyse habitat selection of the badger for the location of setts, our results confirm the importance of the forested area and specifically riverine forests for the badgers in agricultural matrices. Furthermore, it is known that several mammals use the complex burrow system of the European badger as shelter or as a reproductive site. In a highly fragmented and disturbed area, the high density of badger setts could favour the expansion and the survival of other species, some of which are of conservation interest (e.g., European wildcat Felis silvestris and golden jackal Canis aureus) and some other invasive species (e.g., the raccoon dog Nyctereutes procyonoides)