PHEIGES: all-cell-free phage synthesis and selection from engineered genomes.

Bacteriophages constitute an invaluable biological reservoir for biotechnology and medicine. The ability to exploit such vast resources is hampered by the lack of methods to rapidly engineer, assemble, package genomes, and select phages. Cell-free transcription-translation (TXTL) offers experimental settings to address such a limitation. Here, we describe PHage Engineering by In vitro Gene Expression and Selection (PHEIGES) using T7 phage genome and Escherichia coli TXTL. Phage genomes are assembled in vitro from PCR-amplified fragments and directly expressed in batch TXTL reactions to produce up to 1011 PFU/ml engineered phages within one day. We further demonstrate a significant genotype-phenotype linkage of phage assembly in bulk TXTL. This enables rapid selection of phages with altered rough lipopolysaccharides specificity from phage genomes incorporating tail fiber mutant libraries. We establish the scalability of PHEIGES by one pot assembly of such mutants with fluorescent gene integration and 10% length-reduced genome.

Expanding evolutionary theories of ageing to better account for symbioses and interactions throughout the Web of Life.

How, when, and why organisms age are fascinating issues that can only be fully addressed by adopting an evolutionary perspective. Consistently, the main evolutionary theories of ageing, namely the Mutation Accumulation theory, the Antagonistic Pleiotropy theory, and the Disposable Soma theory, have formulated stimulating hypotheses that structure current debates on both the proximal and ultimate causes of organismal ageing. However, all these theories leave a common area of biology relatively under-explored. The Mutation Accumulation theory and the Antagonistic Pleiotropy theory were developed under the traditional framework of population genetics, and therefore are logically centred on the ageing of individuals within a population. The Disposable Soma theory, based on principles of optimising physiology, mainly explains ageing within a species. Consequently, current leading evolutionary theories of ageing do not explicitly model the countless interspecific and ecological interactions, such as symbioses and host-microbiomes associations, increasingly recognized to shape organismal evolution across the Web of Life. Moreover, the development of network modelling supporting a deeper understanding on the molecular interactions associated with ageing within and between organisms is also bringing forward new questions regarding how and why molecular pathways associated with ageing evolved. Here, we take an evolutionary perspective to examine the effects of organismal interactions on ageing across different levels of biological organisation, and consider the impact of surrounding and nested systems on organismal ageing. We also apply this perspective to suggest open issues with potential to expand the standard evolutionary theories of ageing.

Damage dynamics and the role of chance in the timing of E. coli cell death.

Genetically identical cells in the same stressful condition die at different times. The origin of this stochasticity is unclear; it may arise from different initial conditions that affect the time of demise, or from a stochastic damage accumulation mechanism that erases the initial conditions and instead amplifies noise to generate different lifespans. To address this requires measuring damage dynamics in individual cells over the lifespan, but this has rarely been achieved. Here, we used a microfluidic device to measure membrane damage in 635 carbon-starved Escherichia coli cells at high temporal resolution. We find that initial conditions of damage, size or cell-cycle phase do not explain most of the lifespan variation. Instead, the data points to a stochastic mechanism in which noise is amplified by a rising production of damage that saturates its own removal. Surprisingly, the relative variation in damage drops with age: cells become more similar to each other in terms of relative damage, indicating increasing determinism with age. Thus, chance erases initial conditions and then gives way to increasingly deterministic dynamics that dominate the lifespan distribution.

Spatial engineering of E. coli with addressable phase-separated RNAs.

Biochemical processes often require spatial regulation and specific microenvironments. The general lack of organelles in bacteria limits the potential of bioengineering complex intracellular reactions. Here, we demonstrate synthetic membraneless organelles in Escherichia coli termed transcriptionally engineered addressable RNA solvent droplets (TEARS). TEARS are assembled from RNA-binding protein recruiting domains fused to poly-CAG repeats that spontaneously drive liquid-liquid phase separation from the bulk cytoplasm. Targeting TEARS with fluorescent proteins revealed multilayered structures with composition and reaction robustness governed by non-equilibrium dynamics. We show that TEARS provide organelle-like bioprocess isolation for sequestering biochemical pathways, controlling metabolic branch points, buffering mRNA translation rates, and scaffolding protein-protein interactions. We anticipate TEARS to be a simple and versatile tool for spatially controlling E. coli biochemistry. Particularly, the modular design of TEARS enables applications without expression fine-tuning, simplifying the design-build-test cycle of bioengineering.

Low-cost anti-mycobacterial drug discovery using engineered E. coli.

Whole-cell screening for Mycobacterium tuberculosis (Mtb) inhibitors is complicated by the pathogen's slow growth and biocontainment requirements. Here we present a synthetic biology framework for assaying Mtb drug targets in engineered E. coli. We construct Target Essential Surrogate E. coli (TESEC) in which an essential metabolic enzyme is deleted and replaced with an Mtb-derived functional analog, linking bacterial growth to the activity of the target enzyme. High throughput screening of a TESEC model for Mtb alanine racemase (Alr) revealed benazepril as a targeted inhibitor, a result validated in whole-cell Mtb. In vitro biochemical assays indicated a noncompetitive mechanism unlike that of clinical Alr inhibitors. We establish the scalability of TESEC for drug discovery by characterizing TESEC strains for four additional targets.

Bacteria can be selected to help beneficial plasmids spread.

A recent commentary raised concerns about aspects of the model and assumptions used in a previous study which demonstrated that selection can favor chromosomal alleles that confer higher plasmid donation rates. Here, the authors of that previous study respond to the concerns raised.

Remote Digital Psychiatry for Mobile Mental Health Assessment and Therapy: MindLogger Platform Development Study.

BACKGROUND: Universal access to assessment and treatment of mental health and learning disorders remains a significant and unmet need. There are many people without access to care because of economic, geographic, and cultural barriers, as well as the limited availability of clinical experts who could help advance our understanding and treatment of mental health. OBJECTIVE: This study aims to create an open, configurable software platform to build clinical measures, mobile assessments, tasks, and interventions without programming expertise. Specifically, our primary requirements include an administrator interface for creating and scheduling recurring and customized questionnaires where end users receive and respond to scheduled notifications via an iOS or Android app on a mobile device. Such a platform would help relieve overwhelmed health systems and empower remote and disadvantaged subgroups in need of accurate and effective information, assessment, and care. This platform has the potential to advance scientific research by supporting the collection of data with instruments tailored to specific scientific questions from large, distributed, and diverse populations. METHODS: We searched for products that satisfy these requirements. We designed and developed a new software platform called MindLogger, which exceeds the requirements. To demonstrate the platform's configurability, we built multiple applets (collections of activities) within the MindLogger mobile app and deployed several of them, including a comprehensive set of assessments underway in a large-scale, longitudinal mental health study. RESULTS: Of the hundreds of products we researched, we found 10 that met our primary requirements with 4 that support end-to-end encryption, 2 that enable restricted access to individual users' data, 1 that provides open-source software, and none that satisfy all three. We compared features related to information presentation and data capture capabilities; privacy and security; and access to the product, code, and data. We successfully built MindLogger mobile and web applications, as well as web browser-based tools for building and editing new applets and for administering them to end users. MindLogger has end-to-end encryption, enables restricted access, is open source, and supports a variety of data collection features. One applet is currently collecting data from children and adolescents in our mental health study, and other applets are in different stages of testing and deployment for use in clinical and research settings. CONCLUSIONS: We demonstrated the flexibility and applicability of the MindLogger platform through its deployment in a large-scale, longitudinal, mobile mental health study and by building a variety of other mental health-related applets. With this release, we encourage a broad range of users to apply the MindLogger platform to create and test applets to advance health care and scientific research. We hope that increasing the availability of applets designed to assess and administer interventions will facilitate access to health care in the general population.

Engineering gene overlaps to sustain genetic constructs in vivo.

Evolution is often an obstacle to the engineering of stable biological systems due to the selection of mutations inactivating costly gene circuits. Gene overlaps induce important constraints on sequences and their evolution. We show that these constraints can be harnessed to increase the stability of costly genes by purging loss-of-function mutations. We combine computational and synthetic biology approaches to rationally design an overlapping reading frame expressing an essential gene within an existing gene to protect. Our algorithm succeeded in creating overlapping reading frames in 80% of E. coli genes. Experimentally, scoring mutations in both genes of such overlapping construct, we found that a significant fraction of mutations impacting the gene to protect have a deleterious effect on the essential gene. Such an overlap thus protects a costly gene from removal by natural selection by associating the benefit of this removal with a larger or even lethal cost. In our synthetic constructs, the overlap converts many of the possible mutants into evolutionary dead-ends, reducing the evolutionary potential of the system and thus increasing its stability over time.

Accessible LAMP-Enabled Rapid Test (ALERT) for Detecting SARS-CoV-2.

The coronavirus disease 2019 (COVID-19) pandemic has highlighted bottlenecks in large-scale, frequent testing of populations for infections. Polymerase chain reaction (PCR)-based diagnostic tests are expensive, reliant on centralized labs, can take days to deliver results, and are prone to backlogs and supply shortages. Antigen tests that bind and detect the surface proteins of a virus are rapid and scalable but suffer from high false negative rates. To address this problem, an inexpensive, simple, and robust 60-minute do-it-yourself (DIY) workflow to detect viral RNA from nasal swabs or saliva with high sensitivity (0.1 to 2 viral particles/µL) and specificity (>97% true negative rate) utilizing reverse transcription loop-mediated isothermal amplification (RT-LAMP) was developed. ALERT (Accessible LAMP-Enabled Rapid Test) incorporates the following features: (1) increased shelf-life and ambient temperature storage, compared to liquid reaction mixes, by using wax layers to isolate enzymes from other reagents; (2) improved specificity compared to other LAMP end-point reporting methods, by using sequence-specific QUASR (quenching of unincorporated amplification signal reporters); (3) increased sensitivity, compared to methods without purification through use of a magnetic wand to enable pipette-free concentration of sample RNA and cell debris removal; (4) quality control with a nasopharyngeal-specific mRNA target; and (5) co-detection of other respiratory viruses, such as influenza B, by multiplexing QUASR-modified RT-LAMP primer sets. The flexible nature of the ALERT workflow allows easy, at-home and point-of-care testing for individuals and higher-throughput processing for labs and hospitals. With minimal effort, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-specific primer sets can be swapped out for other targets to repurpose ALERT to detect other viruses, microorganisms, or nucleic acid-based markers.

A survival model for course-course interactions in a Massive Open Online Course platform.

Massive Open Online Course (MOOC) platforms incorporate large course catalogs from which individual students may register multiple courses. We performed a network-based analysis of student achievement, considering how course-course interactions may positively or negatively affect student success. Our data set included 378,000 users and 1,000,000 unique registration events in France Université Numérique (FUN), a national MOOC platform. We adapt reliability theory to model certificate completion rates with a Weibull survival function, following the intuition that students "survive" in a course for a certain time before stochastically dropping out. Course-course interactions are found to be well described by a single parameter for user engagement that can be estimated from a user's registration profile. User engagement, in turn, correlates with certificate rates in all courses regardless of specific content. The reliability approach is shown to capture several certificate rate patterns that are overlooked by conventional regression models. User engagement emerges as a natural metric for tracking student progress across demographics and over time.

Loop-Mediated Isothermal Amplification Detection of SARS-CoV-2 and Myriad Other Applications.

As the second year of the COVID-19 pandemic begins, it remains clear that a massive increase in the ability to test for SARS-CoV-2 infections in a myriad of settings is critical to controlling the pandemic and to preparing for future outbreaks. The current gold standard for molecular diagnostics is the polymerase chain reaction (PCR), but the extraordinary and unmet demand for testing in a variety of environments means that both complementary and supplementary testing solutions are still needed. This review highlights the role that loop-mediated isothermal amplification (LAMP) has had in filling this global testing need, providing a faster and easier means of testing, and what it can do for future applications, pathogens, and the preparation for future outbreaks. This review describes the current state of the art for research of LAMP-based SARS-CoV-2 testing, as well as its implications for other pathogens and testing. The authors represent the global LAMP (gLAMP) Consortium, an international research collective, which has regularly met to share their experiences on LAMP deployment and best practices; sections are devoted to all aspects of LAMP testing, including preanalytic sample processing, target amplification, and amplicon detection, then the hardware and software required for deployment are discussed, and finally, a summary of the current regulatory landscape is provided. Included as well are a series of first-person accounts of LAMP method development and deployment. The final discussion section provides the reader with a distillation of the most validated testing methods and their paths to implementation. This review also aims to provide practical information and insight for a range of audiences: for a research audience, to help accelerate research through sharing of best practices; for an implementation audience, to help get testing up and running quickly; and for a public health, clinical, and policy audience, to help convey the breadth of the effect that LAMP methods have to offer.

Corona Detective: a simple, scalable, and robust SARS-CoV-2 detection method based on reverse transcription loop-mediated isothermal amplification.

Surveillance screening at scale to identify people infected by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) prior to extensive transmission is key to bringing an end to the coronavirus disease 2019 (COVID-19) pandemic, even though vaccinations have already begun. Here we describe Corona Detective, a sensitive and rapid molecular test to detect the virus, based on loop-mediated isothermal amplification, which could be applied anywhere at low cost. Critically, the method uses freeze-dried reagents, readily shipped without cold-chain dependence. The reaction detects the viral nucleocapsid gene through a sequence-specific quenched-fluorescence readout, which avoids false positives and also allows multiplex detection with an internal control cellular RNA. Corona Detective can be used in 8-tube strips to be read with a simple open-design fluorescence detector. Other methods to use and produce Corona Detective locally in a variety of formats are possible and already openly shared. Detection specificity is ensured through inclusion of positive and negative control reactions to run in parallel with the diagnostic reactions. A simple user protocol, including sample preparation, and a bioinformatics pipeline to ensure that viral variants will still be detectable with SARS-CoV-2 primer sets complete the method. Through rapid production and distribution of Corona Detective reactions, quite inexpensive at scale, daily or weekly surveillance testing of large populations, without waiting for symptoms to develop, is anticipated, in combination with vaccination campaigns, to finally control this pandemic.

Artificial modulation of cell width significantly affects the division time of Escherichia coli.

Bacterial cells have characteristic spatial and temporal scales. For instance, Escherichia coli, the typical rod-shaped bacteria, always maintains a relatively constant cell width and cell division time. However, whether the external physical perturbation of cell width has an impact on cell division time remains largely unexplored. In this work, we developed two microchannel chips, namely straight channels and 'necked' channels, to precisely regulate the width of E. coli cells and to investigate the correlation between cell width and division time of the cells. Our results show that, in the straight channels, the wide cells divide much slower than narrow cells. In the 'necked' channels, the cell division is remarkably promoted compared to that in straight channels with the same width. Besides, fluorescence time-lapse microscopy imaging of FtsZ dynamics shows that the cell pre-constriction time is more sensitive to cell width perturbation than cell constriction time. Finally, we revealed a significant anticorrelation between the death rate and the division rate of cell populations with different widths. Our work provides new insights into the correlation between the geometrical property and division time of E. coli cells and sheds new light on the future study of spatial-temporal correlation in cell physiology.

Ratiometric quorum sensing governs the trade-off between bacterial vertical and horizontal antibiotic resistance propagation.

Plasmid-mediated horizontal gene transfer of antibiotic resistance and virulence in pathogenic bacteria underlies a major public health issue. Understanding how, in the absence of antibiotic-mediated selection, plasmid-bearing cells avoid being outnumbered by plasmid-free cells is key to developing counterstrategies. Here, we quantified the induction of the plasmidial sex pheromone pathway of Enterococcus faecalis to show that the integration of the stimulatory (mate-sensing) and inhibitory (self-sensing) signaling modules from the pCF10 conjugative plasmid provides a precise measure of the recipient-to-donor ratio, agnostic to variations in population size. Such ratiometric control of conjugation favors vertical plasmid transfer under low mating likelihood and allows activation of conjugation functions only under high mating likelihood. We further show that this strategy constitutes a cost-effective investment into mating effort because overstimulation produces unproductive self-aggregation and growth rate reduction. A mathematical model suggests that ratiometric control of conjugation increases plasmid fitness and predicts a robust long-term, stable coexistence of donors and recipients. Our results demonstrate how population-level parameters can control transfer of antibiotic resistance in bacteria, opening the door for biotic control strategies.

Observing Nutrient Gradients, Gene Expression and Growth Variation Using the "Yeast Machine" Microfluidic Device.

The natural environment of microbial cells like bacteria and yeast is often a complex community in which growth and internal organization reflect morphogenetic processes and interactions that are dependent on spatial position and time. While most of research is performed in simple homogeneous environments (e.g., bulk liquid cultures), which cannot capture full spatiotemporal community dynamics, studying biofilms or colonies is complex and usually does not give access to the spatiotemporal dynamics at single cell level. Here, we detail a protocol for generation of a microfluidic device, the "yeast machine", with arrays of long monolayers of yeast colonies to advance the global understanding of how intercellular metabolic interactions affect the internal structure of colonies within defined and customizable spatial dimensions. With Saccharomyces cerevisiae as a model yeast system we used the "yeast machine" to demonstrate the emergence of glucose gradients by following expression of fluorescently labelled hexose transporters. We further quantified the expression spatial patterns with intra-colony growth rates and expression of other genes regulated by glucose availability. In addition to this, we showed that gradients of amino acids also form within a colony, potentially opening similar approaches to study spatiotemporal formation of gradients of many other nutrients and metabolic waste products. This approach could be used in the future to decipher the interplay between long-range metabolic interactions, cellular development, and morphogenesis in other same species or more complex multi-species systems at single-cell resolution and timescales relevant to ecology and evolution.

A microfluidic device for inferring metabolic landscapes in yeast monolayer colonies.

Microbial colonies are fascinating structures in which growth and internal organization reflect complex morphogenetic processes. Here, we generated a microfluidics device with arrays of long monolayer yeast colonies to further global understanding of how intercellular metabolic interactions affect the internal structure of colonies within defined boundary conditions. We observed the emergence of stable glucose gradients using fluorescently labeled hexose transporters and quantified the spatial correlations with intra-colony growth rates and expression of other genes regulated by glucose availability. These landscapes depended on the external glucose concentration as well as secondary gradients, for example amino acid availability. This work demonstrates the regulatory genetic networks governing cellular physiological adaptation are the key to internal structuration of cellular assemblies. This approach could be used in the future to decipher the interplay between long-range metabolic interactions, cellular development and morphogenesis in more complex systems.

Systematic Detection of Amino Acid Substitutions in Proteomes Reveals Mechanistic Basis of Ribosome Errors and Selection for Translation Fidelity.

The translation machinery and the genes it decodes co-evolved to achieve production throughput and accuracy. Nonetheless, translation errors are frequent, and they affect physiology and protein evolution. Mapping translation errors in proteomes and understanding their causes is hindered by lack of a proteome-wide experimental methodology. We present the first methodology for systematic detection and quantification of errors in entire proteomes. Following proteome mass spectrometry, we identify, in E. coli and yeast, peptides whose mass indicates specific amino acid substitutions. Most substitutions result from codon-anticodon mispairing. Errors occur at sites that evolve rapidly and that minimally affect energetic stability, indicating selection for high translation fidelity. Ribosome density data show that errors occur at sites where ribosome velocity is higher, demonstrating a trade-off between speed and accuracy. Treating bacteria with an aminoglycoside antibiotic or deprivation of specific amino acids resulted in particular patterns of errors. These results reveal a mechanistic and evolutionary basis for translation fidelity.

Temporal scaling of aging as an adaptive strategy of Escherichia coli.

Natural selection is thought to shape the evolution of aging patterns, although how life-history trajectories orchestrate the inherently stochastic processes associated with aging is unclear. Tracking clonal growth-arrested Escherichia coli cohorts in an homogeneous environment at single-cell resolution, we demonstrate that the Gompertz law of exponential mortality characterizes bacterial lifespan distributions. By disentangling the rate of aging from age-independent components of longevity, we find that increasing cellular maintenance through the general stress pathway reduces the aging rate and rescales the lifespan distribution at the expense of growth. This trade-off between aging and growth underpins the evolutionary tuning of the general stress response pathway in adaptation to the organism's feast-or-famine lifestyle. It is thus necessary to involve both natural selection and stochastic physiology to explain aging patterns.

Two stochastic processes shape diverse senescence patterns in a single-cell organism.

Despite advances in aging research, a multitude of aging models, and empirical evidence for diverse senescence patterns, understanding of the biological processes that shape senescence is lacking. We show that senescence of an isogenic Escherichia coli bacterial population results from two stochastic processes. The first process is a random deterioration process within the cell, such as generated by random accumulation of damage. This primary process leads to an exponential increase in mortality early in life followed by a late age mortality plateau. The second process relates to the stochastic asymmetric transmission at cell fission of an unknown factor that influences mortality. This secondary process explains the difference between the classical mortality plateaus detected for young mothers' offspring and the near nonsenescence of old mothers' offspring as well as the lack of a mother-offspring correlation in age at death. We observed that lifespan is predominantly determined by underlying stochastic stage dynamics. Surprisingly, our findings support models developed for metazoans that base their arguments on stage-specific actions of alleles to understand the evolution of senescence. We call for exploration of similar stochastic influences that shape aging patterns beyond simple organisms.