The transcription factor titration effect dictates level of gene expression.

Models of transcription are often built around a picture of RNA polymerase and transcription factors (TFs) acting on a single copy of a promoter. However, most TFs are shared between multiple genes with varying binding affinities. Beyond that, genes often exist at high copy number-in multiple identical copies on the chromosome or on plasmids or viral vectors with copy numbers in the hundreds. Using a thermodynamic model, we characterize the interplay between TF copy number and the demand for that TF. We demonstrate the parameter-free predictive power of this model as a function of the copy number of the TF and the number and affinities of the available specific binding sites; such predictive control is important for the understanding of transcription and the desire to quantitatively design the output of genetic circuits. Finally, we use these experiments to dynamically measure plasmid copy number through the cell cycle.

Building enhancers from the ground up: a synthetic biology approach.

A challenge of the synthetic biology approach is to use our understanding of a system to recreate a biological function with specific properties. We have applied this framework to bacterial enhancers, combining a driver, transcription factor binding sites, and a poised polymerase to create synthetic modular enhancers. Our findings suggest that enhancer-based transcriptional control depends critically and quantitatively on DNA looping, leading to complex regulatory effects when the enhancer cassettes contain additional transcription factor binding sites for TetR, a bacterial transcription factor. We show through a systematic interplay of experiment and thermodynamic modeling that the level of gene expression can be modulated to convert a variable inducer concentration input into discrete or step-like output expression levels. Finally, using a different DNA-binding protein (TraR), we show that the regulatory output is not a particular feature of the specific DNA-binding protein used for the enhancer but a general property of synthetic bacterial enhancers.

Controlling organization and forces in active matter through optically defined boundaries.

Living systems are capable of locomotion, reconfiguration and replication. To perform these tasks, cells spatiotemporally coordinate the interactions of force-generating, 'active' molecules that create and manipulate non-equilibrium structures and force fields of up to millimetre length scales1-3. Experimental active-matter systems of biological or synthetic molecules are capable of spontaneously organizing into structures4,5 and generating global flows6-9. However, these experimental systems lack the spatiotemporal control found in cells, limiting their utility for studying non-equilibrium phenomena and bioinspired engineering. Here we uncover non-equilibrium phenomena and principles of boundary-mediated control by optically modulating structures and fluid flow in an engineered system of active biomolecules. Our system consists of purified microtubules and light-activatable motor proteins that crosslink and organize the microtubules into distinct structures upon illumination. We develop basic operations-defined as sets of light patterns-to create, move and merge the microtubule structures. By combining these operations, we create microtubule networks that span several hundred micrometres in length and contract at speeds up to an order of magnitude higher than the speed of an individual motor protein. We manipulate these contractile networks to generate and sculpt persistent fluid flows. The principles of boundary-mediated control that we uncover may be used to study emergent cellular structures and forces and to develop programmable active-matter devices.

The total number and mass of SARS-CoV-2 virions.

Quantitatively describing the time course of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection within an infected individual is important for understanding the current global pandemic and possible ways to combat it. Here we integrate the best current knowledge about the typical viral load of SARS-CoV-2 in bodily fluids and host tissues to estimate the total number and mass of SARS-CoV-2 virions in an infected person. We estimate that each infected person carries 109 to 1011 virions during peak infection, with a total mass in the range of 1 µg to 100 µg, which curiously implies that all SARS-CoV-2 virions currently circulating within human hosts have a collective mass of only 0.1 kg to 10 kg. We combine our estimates with the available literature on host immune response and viral mutation rates to demonstrate how antibodies markedly outnumber the spike proteins, and the genetic diversity of virions in an infected host covers all possible single nucleotide substitutions.

MCRL: using a reference library to compress a metagenome into a non-redundant list of sequences, considering viruses as a case study.

MOTIVATION: Metagenomes offer a glimpse into the total genomic diversity contained within a sample. Currently, however, there is no straightforward way to obtain a non-redundant list of all putative homologs of a set of reference sequences present in a metagenome. RESULTS: To address this problem, we developed a novel clustering approach called 'metagenomic clustering by reference library' (MCRL), where a reference library containing a set of reference genes is clustered with respect to an assembled metagenome. According to our proposed approach, reference genes homologous to similar sets of metagenomic sequences, termed 'signatures', are iteratively clustered in a greedy fashion, retaining at each step the reference genes yielding the lowest E values, and terminating when signatures of remaining reference genes have a minimal overlap. The outcome of this computation is a non-redundant list of reference genes homologous to minimally overlapping sets of contigs, representing potential candidates for gene families present in the metagenome. Unlike metagenomic clustering methods, there is no need for contigs to overlap to be associated with a cluster, enabling MCRL to draw on more information encoded in the metagenome when computing tentative gene families. We demonstrate how MCRL can be used to extract candidate viral gene families from an oral metagenome and an oral virome that otherwise could not be determined using standard approaches. We evaluate the sensitivity, accuracy and robustness of our proposed method for the viral case study and compare it with existing analysis approaches. AVAILABILITY AND IMPLEMENTATION: https://github.com/a-tadmor/MCRL. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Reconciling kinetic and thermodynamic models of bacterial transcription.

The study of transcription remains one of the centerpieces of modern biology with implications in settings from development to metabolism to evolution to disease. Precision measurements using a host of different techniques including fluorescence and sequencing readouts have raised the bar for what it means to quantitatively understand transcriptional regulation. In particular our understanding of the simplest genetic circuit is sufficiently refined both experimentally and theoretically that it has become possible to carefully discriminate between different conceptual pictures of how this regulatory system works. This regulatory motif, originally posited by Jacob and Monod in the 1960s, consists of a single transcriptional repressor binding to a promoter site and inhibiting transcription. In this paper, we show how seven distinct models of this so-called simple-repression motif, based both on thermodynamic and kinetic thinking, can be used to derive the predicted levels of gene expression and shed light on the often surprising past success of the thermodynamic models. These different models are then invoked to confront a variety of different data on mean, variance and full gene expression distributions, illustrating the extent to which such models can and cannot be distinguished, and suggesting a two-state model with a distribution of burst sizes as the most potent of the seven for describing the simple-repression motif.

Sequence-dependent dynamics of synthetic and endogenous RSSs in V(D)J recombination.

Developing lymphocytes of jawed vertebrates cleave and combine distinct gene segments to assemble antigen-receptor genes. This process called V(D)J recombination that involves the RAG recombinase binding and cutting recombination signal sequences (RSSs) composed of conserved heptamer and nonamer sequences flanking less well-conserved 12- or 23-bp spacers. Little quantitative information is known about the contributions of individual RSS positions over the course of the RAG-RSS interaction. We employ a single-molecule method known as tethered particle motion to track the formation, lifetime and cleavage of individual RAG-12RSS-23RSS paired complexes (PCs) for numerous synthetic and endogenous 12RSSs. We reveal that single-bp changes, including in the 12RSS spacer, can significantly and selectively alter PC formation or the probability of RAG-mediated cleavage in the PC. We find that some rarely used endogenous gene segments can be mapped directly to poor RAG binding on their adjacent 12RSSs. Finally, we find that while abrogating RSS nicking with Ca2+ leads to substantially shorter PC lifetimes, analysis of the complete lifetime distributions of any 12RSS even on this reduced system reveals that the process of exiting the PC involves unidentified molecular details whose involvement in RAG-RSS dynamics are crucial to quantitatively capture kinetics in V(D)J recombination.

How the avidity of polymerase binding to the -35/-10 promoter sites affects gene expression.

Although the key promoter elements necessary to drive transcription in Escherichia coli have long been understood, we still cannot predict the behavior of arbitrary novel promoters, hampering our ability to characterize the myriad sequenced regulatory architectures as well as to design new synthetic circuits. This work builds upon a beautiful recent experiment by Urtecho et al. [G. Urtecho, et al, Biochemistry, 68, 1539-1551 (2019)] who measured the gene expression of over 10,000 promoters spanning all possible combinations of a small set of regulatory elements. Using these data, we demonstrate that a central claim in energy matrix models of gene expression-that each promoter element contributes independently and additively to gene expression-contradicts experimental measurements. We propose that a key missing ingredient from such models is the avidity between the -35 and -10 RNA polymerase binding sites and develop what we call a multivalent model that incorporates this effect and can successfully characterize the full suite of gene expression data. We explore several applications of this framework, namely, how multivalent binding at the -35 and -10 sites can buffer RNA polymerase (RNAP) kinetics against mutations and how promoters that bind overly tightly to RNA polymerase can inhibit gene expression. The success of our approach suggests that avidity represents a key physical principle governing the interaction of RNA polymerase to its promoter.

Torque-dependent remodeling of the bacterial flagellar motor.

Multisubunit protein complexes are ubiquitous in biology and perform a plethora of essential functions. Most of the scientific literature treats such assemblies as static: their function is assumed to be independent of their manner of assembly, and their structure is assumed to remain intact until they are degraded. Recent observations of the bacterial flagellar motor, among others, bring these notions into question. The torque-generating stator units of the motor assemble and disassemble in response to changes in load. Here, we used electrorotation to drive tethered cells forward, which decreases motor load, and measured the resulting stator dynamics. No disassembly occurred while the torque remained high, but all of the stator units were released when the motor was spun near the zero-torque speed. When the electrorotation was turned off, so that the load was again high, stator units were recruited, increasing motor speed in a stepwise fashion. A model in which speed affects the binding rate and torque affects the free energy of bound stator units captures the observed torque-dependent stator assembly dynamics, providing a quantitative framework for the environmentally regulated self-assembly of a major macromolecular machine.

Predictive shifts in free energy couple mutations to their phenotypic consequences.

Mutation is a critical mechanism by which evolution explores the functional landscape of proteins. Despite our ability to experimentally inflict mutations at will, it remains difficult to link sequence-level perturbations to systems-level responses. Here, we present a framework centered on measuring changes in the free energy of the system to link individual mutations in an allosteric transcriptional repressor to the parameters which govern its response. We find that the energetic effects of the mutations can be categorized into several classes which have characteristic curves as a function of the inducer concentration. We experimentally test these diagnostic predictions using the well-characterized LacI repressor of Escherichia coli, probing several mutations in the DNA binding and inducer binding domains. We find that the change in gene expression due to a point mutation can be captured by modifying only the model parameters that describe the respective domain of the wild-type protein. These parameters appear to be insulated, with mutations in the DNA binding domain altering only the DNA affinity and those in the inducer binding domain altering only the allosteric parameters. Changing these subsets of parameters tunes the free energy of the system in a way that is concordant with theoretical expectations. Finally, we show that the induction profiles and resulting free energies associated with pairwise double mutants can be predicted with quantitative accuracy given knowledge of the single mutants, providing an avenue for identifying and quantifying epistatic interactions.

The biomass distribution on Earth.

A census of the biomass on Earth is key for understanding the structure and dynamics of the biosphere. However, a global, quantitative view of how the biomass of different taxa compare with one another is still lacking. Here, we assemble the overall biomass composition of the biosphere, establishing a census of the ≈550 gigatons of carbon (Gt C) of biomass distributed among all of the kingdoms of life. We find that the kingdoms of life concentrate at different locations on the planet; plants (≈450 Gt C, the dominant kingdom) are primarily terrestrial, whereas animals (≈2 Gt C) are mainly marine, and bacteria (≈70 Gt C) and archaea (≈7 Gt C) are predominantly located in deep subsurface environments. We show that terrestrial biomass is about two orders of magnitude higher than marine biomass and estimate a total of ≈6 Gt C of marine biota, doubling the previous estimated quantity. Our analysis reveals that the global marine biomass pyramid contains more consumers than producers, thus increasing the scope of previous observations on inverse food pyramids. Finally, we highlight that the mass of humans is an order of magnitude higher than that of all wild mammals combined and report the historical impact of humanity on the global biomass of prominent taxa, including mammals, fish, and plants.

Systematic approach for dissecting the molecular mechanisms of transcriptional regulation in bacteria.

Gene regulation is one of the most ubiquitous processes in biology. However, while the catalog of bacterial genomes continues to expand rapidly, we remain ignorant about how almost all of the genes in these genomes are regulated. At present, characterizing the molecular mechanisms by which individual regulatory sequences operate requires focused efforts using low-throughput methods. Here, we take a first step toward multipromoter dissection and show how a combination of massively parallel reporter assays, mass spectrometry, and information-theoretic modeling can be used to dissect multiple bacterial promoters in a systematic way. We show this approach on both well-studied and previously uncharacterized promoters in the enteric bacterium Escherichia coli In all cases, we recover nucleotide-resolution models of promoter mechanism. For some promoters, including previously unannotated ones, the approach allowed us to further extract quantitative biophysical models describing input-output relationships. Given the generality of the approach presented here, it opens up the possibility of quantitatively dissecting the mechanisms of promoter function in E. coli and a wide range of other bacteria.

Mapping DNA sequence to transcription factor binding energy in vivo.

Despite the central importance of transcriptional regulation in biology, it has proven difficult to determine the regulatory mechanisms of individual genes, let alone entire gene networks. It is particularly difficult to decipher the biophysical mechanisms of transcriptional regulation in living cells and determine the energetic properties of binding sites for transcription factors and RNA polymerase. In this work, we present a strategy for dissecting transcriptional regulatory sequences using in vivo methods (massively parallel reporter assays) to formulate quantitative models that map a transcription factor binding site's DNA sequence to transcription factor-DNA binding energy. We use these models to predict the binding energies of transcription factor binding sites to within 1 kBT of their measured values. We further explore how such a sequence-energy mapping relates to the mechanisms of trancriptional regulation in various promoter contexts. Specifically, we show that our models can be used to design specific induction responses, analyze the effects of amino acid mutations on DNA sequence preference, and determine how regulatory context affects a transcription factor's sequence specificity.

Correction to: Maternal Hypertension, Advanced Doppler Haemodynamics and Therapeutic Precision: Principles and Illustrative Cases.

The original publication of this article, unfortunately, contains the following errors.

Maternal Hypertension, Advanced Doppler Haemodynamics and Therapeutic Precision: Principles and Illustrative Cases.

PURPOSE OF REVIEW: Maternal hypertension is a common and serious condition associated with increased maternal and foetal morbidity and mortality, with early detection and management improving outcomes. RECENT FINDINGS: Blood pressure (BP) changes of pre-eclampsia are defined after 20 gestational weeks, while haemodynamic changes can be detected at 5-11 weeks using a specialised non-invasive Doppler stroke volume (SV) monitor. Thus, advanced haemodynamic monitoring allows for physiologically precise identification of circulatory abnormalities, and implementation of appropriate therapy within the first trimester. We measured the oscillometric BP and advanced haemodynamics (USCOM 1A) of 3 unselected women with singleton pregnancies, consecutively listed for therapeutic induction for maternal hypertension at 32-41 weeks gestational age. While the BP's of the patients varied, it was the haemodynamics, particularly SV, cardiac output, systemic vascular resistance, Smith Madigan Inotropy Index, and oxygen deliver, that identified differing patterns of circulatory dysfunction, therapeutic objectives, and predicted post-partum complications of the mother and child. First trimester screening of maternal haemodynamics may allow for earlier detection of circulatory derangements, selection of patient precise interventions, and improved maternal-foetal outcomes.

Energetic cost of building a virus.

Viruses are incapable of autonomous energy production. Although many experimental studies make it clear that viruses are parasitic entities that hijack the molecular resources of the host, a detailed estimate for the energetic cost of viral synthesis is largely lacking. To quantify the energetic cost of viruses to their hosts, we enumerated the costs associated with two very distinct but representative DNA and RNA viruses, namely, T4 and influenza. We found that, for these viruses, translation of viral proteins is the most energetically expensive process. Interestingly, the costs of building a T4 phage and a single influenza virus are nearly the same. Due to influenza's higher burst size, however, the overall cost of a T4 phage infection is only 2-3% of the cost of an influenza infection. The costs of these infections relative to their host's estimated energy budget during the infection reveal that a T4 infection consumes about a third of its host's energy budget, whereas an influenza infection consumes only ≈ 1%. Building on our estimates for T4, we show how the energetic costs of double-stranded DNA phages scale with the capsid size, revealing that the dominant cost of building a virus can switch from translation to genome replication above a critical size. Last, using our predictions for the energetic cost of viruses, we provide estimates for the strengths of selection and genetic drift acting on newly incorporated genetic elements in viral genomes, under conditions of energy limitation.

Connecting the Dots between Mechanosensitive Channel Abundance, Osmotic Shock, and Survival at Single-Cell Resolution.

Rapid changes in extracellular osmolarity are one of many insults microbial cells face on a daily basis. To protect against such shocks, Escherichia coli and other microbes express several types of transmembrane channels that open and close in response to changes in membrane tension. In E. coli, one of the most abundant channels is the mechanosensitive channel of large conductance (MscL). While this channel has been heavily characterized through structural methods, electrophysiology, and theoretical modeling, our understanding of its physiological role in preventing cell death by alleviating high membrane tension remains tenuous. In this work, we examine the contribution of MscL alone to cell survival after osmotic shock at single-cell resolution using quantitative fluorescence microscopy. We conducted these experiments in an E. coli strain which is lacking all mechanosensitive channel genes save for MscL, whose expression was tuned across 3 orders of magnitude through modifications of the Shine-Dalgarno sequence. While theoretical models suggest that only a few MscL channels would be needed to alleviate even large changes in osmotic pressure, we find that between 500 and 700 channels per cell are needed to convey upwards of 80% survival. This number agrees with the average MscL copy number measured in wild-type E. coli cells through proteomic studies and quantitative Western blotting. Furthermore, we observed zero survival events in cells with fewer than ∼100 channels per cell. This work opens new questions concerning the contribution of other mechanosensitive channels to survival, as well as regulation of their activity.IMPORTANCE Mechanosensitive (MS) channels are transmembrane protein complexes which open and close in response to changes in membrane tension as a result of osmotic shock. Despite extensive biophysical characterization, the contribution of these channels to cell survival remains largely unknown. In this work, we used quantitative video microscopy to measure the abundance of a single species of MS channel in single cells, followed by their survival after a large osmotic shock. We observed total death of the population with fewer than ∼100 channels per cell and determined that approximately 500 to 700 channels were needed for 80% survival. The number of channels we found to confer nearly full survival is consistent with the counts of the numbers of channels in wild-type cells in several earlier studies. These results prompt further studies to dissect the contribution of other channel species to survival.

Musings on mechanism: quest for a quark theory of proteins?

The give and take between biology and physics is an important part of the history of modern science, with this partnership perhaps now more intimate than ever. In this essay, I explore the ways in which these different fields can strengthen each other through their distinct outlooks on some of the most important questions being asked about the living world. In particular, I highlight three areas where the perspective from physics might lead to deeper insights into the workings of cells. First, I consider what it means for two ostensibly unrelated problems to be the same, and how such sameness can provide unexpected insights into apparently unrelated phenomena. Second, I consider different conceptions of what constitutes a mechanistic understanding of a given phenomenon with an emphasis on nonmolecular notions of mechanism. The third idea is the importance of "toy problems" as a way of providing foundational insights into the real problems. Though my focus here is primarily on ways in which physics approaches might prove interesting in biology, I close with an example of how biology might substantially alter physics by providing a forum and the tools to uncover a fundamental understanding of nonequilibrium phenomena.-Phillips, R. Musings on mechanism: quest for a quark theory of proteins?