Biology subjects

Ciandrini, L.

Publications and source records attributed to Ciandrini, L..

8 recordsLinked to original sources

bioRxiv2025

Universal sublinear population growth density dependence unrelated to resource limitation

Growth slows as population density increases, sensitively influencing species coexistence, conservation, and resource management. This slowdown is widely attributed to declining per-capita access to energy and nutrients, and standard models of resource-limited growth predict superlinear declines of growth rate with density. However, we observed sublinear declines for 94% of 4,022 bacterial and eukaryotic growth curves. High-resolution experiments with Escherichia coli revealed a two-phase density dependence: a dominant sublinear regime that transitions to superlinear decline only very near population saturation. The sublinear pattern was invariant across initial resource concentrations, ruling out resource depletion as the cause of early slowing. Our results challenge the standard resource-limitation paradigm and identify non-resource inhibitory processes as a widespread and previously unappreciated regulator of population growth.

ecology↗

bioRxiv2025

Uncovering the thermodynamic principles of enzymaticregulation in biomolecular condensates with reactivesimulations

Biomolecular condensates are dynamic cellular assemblies stabilized by weak intermolecular interactions. Cells regulate condensate formation, composition, and function through energy-consuming processes such as post-translational modifications (PTMs), which modify the physicochemical properties of condensate components, thereby dynamically reshaping these interactions. Here, we investigate how enzymatic reactions regulate phase-separated systems using a thermodynamically consistent particle-based model, which allows sampling of out-of-equilibrium steady states. We find that reaction kinetics are intrinsically coupled to the local molecular environment, leading to the formulation of two general principles. First, reactions that weaken favorable interactions are thermodynamically suppressed within condensates. As a consequence, regulation of condensate solubility is most efficient when PTMs tune interactions to values close to the solubility threshold. In contrast, reaction rates are generally enhanced at condensate interfaces, where the thermodynamic inhibition is relieved, but reactant availability remains high. Higher-resolution simulations of FUS and DDX4 proteins indicate that this interfacial contribution remains substantial even for micron-sized condensates, positioning interfaces as key determinants of biochemical activity in phase-separated systems alongside the properties of the condensate bulk. Together, these findings identify general, thermodynamic principles that govern the regulation of biomolecular condensates and link enzymatic activity with phase separation. Moreover, they provide a thermodynamically consistent molecular framework that can be applied to a broad range of regulatory processes in active phase-separated systems.

biophysics↗

bioRxiv2023

How total mRNA influences cell growth

Experimental observations tracing back to the 1960s imply that ribosome quantities play a prominent role in determining a cells growth. Nevertheless, in biologically relevant scenarios, growth can also be influenced by the levels of mRNA and RNA polymerase. Here, we construct a quantitative model of biosynthesis providing testable scenarios for these situations. The model explores a theoretically-motivated regime where RNA polymerases compete for genes and ribosomes for transcripts, and gives general expressions relating growth rate, mRNA concentrations, ribosome and RNA polymerase levels. On general grounds, the model predicts how the fraction of ribosomes in the proteome depends on total mRNA concentration, and inspects an underexplored regime in which the trade-off between transcript levels and ribosome abundances sets the cellular growth rate. In particular, we show that the model predicts and clarifies three important experimental observations, in budding yeast and E. coli bacteria: (i) that the growth-rate cost of unneeded protein expression can be affected by mRNA levels, (ii) that resource optimization leads to decreasing trends in mRNA levels at slow growth, and (iii) that ribosome allocation may increase, stay constant, or decrease, in response to transcription-inhibiting antibiotics. Since the data indicate that a regime of joint limitation may apply in physiological conditions and not only to perturbations, we speculate that this regime is likely self-imposed.

systems biology↗

bioRxiv2021

Role of protein degradation in growth laws

Growing cells adopt common basic strategies to achieve optimal resource allocation under limited resource availability. Our current understanding of such "growth laws" neglects degradation, assuming that it occurs slowly compared to the cell cycle duration. Here we argue that this assumption cannot hold at slow growth, leading to important consequences. We propose a simple framework showing that at slow growth protein degradation is balanced by a fraction of "maintenance" ribosomes. Consequently, active ribosomes do not drop to zero at vanishing growth, but as growth rate diminishes, an increasing fraction of active ribosomes performs maintenance. Through a detailed analysis of compiled data, we show that the predictions of this model agree with data from E. coli and S. cerevisiae. Intriguingly, we also find that protein degradation increases at slow growth, which we interpret as a consequence of active waste management and/or recycling. Our results highlight protein turnover as an underrated factor for our understanding of growth laws across kingdoms. Author summaryThe idea that simple quantitative relationships relate cell physiology to cellular composition dates back to the 1950s, but the recent years saw a leap in our understanding of such "growth laws", with relevant implications regarding the interdependence between growth, metabolism and biochemical networks. However, recent works on nutrient-limited growth mainly focused on laboratory conditions that are favourable to growth. Thus, our current mathematical understanding of the growth laws neglects protein degradation, under the argument that it occurs slowly compared to the timescale of the cell cycle. Instead, at slow growth the timescales of mass loss from protein degradation and dilution become comparable. In this work, we propose that protein degradation shapes the quantitative relationships between ribosome allocation and growth rate, and determines a fraction of ribosomes that do not contribute to growth and need to remain active to balance degradation.

systems biology↗

bioRxiv2020

Unraveling molecular interactions in a phase-separating protein by atomistic simulations

Membraneless organelles are dynamical cellular condensates formed by the liquid-liquid phase separation of proteins and RNA molecules. Multiple evidence suggests that disordered proteins are structural scaffolds that drive the condensation by forming a dynamic network of inter- and intra-molecular contacts. Despite the blooming research activity in this field, the structural characterization of these condensates is very limited and we still do not understand how the phase behaviour is encoded in the amino-acid sequences of the scaffolding proteins. Here we exploited explicit-solvent atomistic simulations to disentangle the molecular interactions governing the phase behaviour of the N-terminal disordered region of DEAD-box helicase 4 (NDDX4), which is a well-established model for phase separation in vitro and in vivo. Single-molecule simulations clarified the interplay between the intramolecular interactions that shape NDDX4 conformational ensemble and the known determinants of its phase behaviour, such as the attraction between oppositely-charged regions and the presence of arginine and phenylalanine. We then investigated intermolecular interactions associated with phase separation via a divide-and-conquer strategy based on the simulations of various NDDX4 fragments at high concentration. Our approach allowed us to probe conditions mimicking real condensates and revealed, in agreement with mutagenesis results, how these interactions arise from the complex interplay of diverse molecular mechanisms. Particularly, we characterized the transient formation of clusters of arginine and aromatic residues, which may stabilize the assembly of several MLOs. Overall, our results reveal the potential of atomistic simulations in the investigation of biomolecular phase separation paving the way for future studies.

biophysics↗

bioRxiv2019

Accurate measures of translation efficiency and traffic using ribosome profiling

One of the main goals of ribosome profiling is to quantify the rate of protein synthesis at the level of translation. Here, we develop a method for inferring translation elongation kinetics from ribosome profiling data using recent advances in the mathematical modelling of mRNA translation. Our method distinguishes between the elongation rate intrinsic to the ribosomes stepping cycle and the actual elongation rate that takes into account ribosome interference. This distinction allows us to quantify the extent of ribosomal collisions along the transcript and identify individual codons where ribosomal collisions are likely. When examining ribosome profiling in yeast, we observe that translation initiation and elongation are close to their optima, and traffic is minimised at the beginning of the transcript to favour ribosome recruitment. However, we find many individual sites of congestion along the mRNAs where the probability of ribosome interference can reach 50%. Our work provides new measures of translation initiation and elongation efficiencies, emphasising the importance of rating these two stages of translation separately.

systems biology↗

bioRxiv2019

Rational programming of history-dependent logic in cellular populations.

Genetic programs operating in an history-dependent fashion are ubiquitous in nature and govern sophisticated processes such as development and differentiation. The ability to systematically and predictably encode such programs would advance the engineering of synthetic organisms and ecosystems with rich signal processing abilities. Here we implement robust, scalable history-dependent programs by distributing the computational labor across a cellular population. Our design is based on recombinase-driven DNA scaffolds expressing different genes according to the order of occurrence of inputs. These multicellular computing systems are highly modular and any program can be built by differential composition of strains containing well-characterized logic scaffolds. We developed an automated workflow that researchers can use to streamline program design and optimization. We anticipate that the history-dependent programs presented here will support many applications using cellular populations for material engineering, biomanufacturing and healthcare.\n\nOne Sentence SummarySystematic and automated frameworks for implementing robust history-dependent genetic programs in cellular populations.

synthetic biology↗

bioRxiv2017

Gene length as a regulator for ribosome recruitmentand protein synthesis: theoretical insights

Protein synthesis rates are determined, at the translational level, by properties of the transcripts sequence. The efficiency of an mRNA can be tuned by varying the ribosome binding sites controlling the recruitment of the ribosomes, or the codon usage establishing the speed of protein elongation. In this work we propose transcript length as a further key determinant of translation efficiency. Based on a physical model that considers the kinetics of ribosomes advancing on the mRNA and diffusing in its surrounding, as well as mRNA circularisation and ribosome drop-off, we explain how the transcript length may play a central role in establishing ribosome recruitment and the overall translation rate of an mRNA. We also demonstrate how this process may be involved in shaping the experimental ribosome density-gene length dependence. Finally, we argue that cells could exploit this mechanism to adjust and balance the usage of its ribosomal resources.

systems biology↗