A data analysis framework for combining multiple batches increases the power of isobaric proteomics experiments.

We present a framework for the analysis of multiplexed mass spectrometry proteomics data that reduces estimation error when combining multiple isobaric batches. Variations in the number and quality of observations have long complicated the analysis of isobaric proteomics data. Here we show that the power to detect statistical associations is substantially improved by utilizing models that directly account for known sources of variation in the number and quality of observations that occur across batches.In a multibatch benchmarking experiment, our open-source software (msTrawler) increases the power to detect changes, especially in the range of less than twofold changes, while simultaneously increasing quantitative proteome coverage by utilizing more low-signal observations. Further analyses of previously published multiplexed datasets of 4 and 23 batches highlight both increased power and the ability to navigate complex missing data patterns without relying on unverifiable imputations or discarding reliable measurements.

High-throughput quantification of microbial birth and death dynamics using fluorescence microscopy.

BACKGROUND: Microbes live in dynamic environments where nutrient concentrations fluctuate. Quantifying fitness in terms of birth rate and death rate in a wide range of environments is critical for understanding microbial evolution and ecology. METHODS: Here, using high-throughput time-lapse microscopy, we have quantified how Saccharomyces cerevisiae mutants incapable of synthesizing an essential metabolite (auxotrophs) grow or die in various concentrations of the required metabolite. We establish that cells normally expressing fluorescent proteins lose fluorescence upon death and that the total fluorescence in an imaging frame is proportional to the number of live cells even when cells form multiple layers. We validate our microscopy approach of measuring birth and death rates using flow cytometry, cell counting, and chemostat culturing. RESULTS: For lysine-requiring cells, very low concentrations of lysine are not detectably consumed and do not support cell birth, but delay the onset of death phase and reduce the death rate compared to no lysine. In contrast, in low hypoxanthine, hypoxanthine-requiring cells can produce new cells, yet also die faster than in the absence of hypoxanthine. For both strains, birth rates under various metabolite concentrations are better described by the sigmoidal-shaped Moser model than the well-known Monod model, while death rates can vary with metabolite concentration and time. CONCLUSIONS: Our work reveals how time-lapse microscopy can be used to discover non-intuitive microbial birth and death dynamics and to quantify growth rates in many environments.

Diversifying the structure of zinc finger nucleases for high-precision genome editing.

Genome editing for therapeutic applications often requires cleavage within a narrow sequence window. Here, to enable such high-precision targeting with zinc-finger nucleases (ZFNs), we have developed an expanded set of architectures that collectively increase the configurational options available for design by a factor of 64. These new architectures feature the functional attachment of the FokI cleavage domain to the amino terminus of one or both zinc-finger proteins (ZFPs) in the ZFN dimer, as well as the option to skip bases between the target triplets of otherwise adjacent fingers in each zinc-finger array. Using our new architectures, we demonstrate targeting of an arbitrarily chosen 28 bp genomic locus at a density that approaches 1.0 (i.e., efficient ZFNs available for targeting almost every base step). We show that these new architectures may be used for targeting three loci of therapeutic significance with a high degree of precision, efficiency, and specificity.

Behavioral Variability and Phenotypic Diversity in Bacterial Chemotaxis.

Living cells detect and process external signals using signaling pathways that are affected by random fluctuations. These variations cause the behavior of individual cells to fluctuate over time (behavioral variability) and generate phenotypic differences between genetically identical individuals (phenotypic diversity). These two noise sources reduce our ability to predict biological behavior because they diversify cellular responses to identical signals. Here, we review recent experimental and theoretical advances in understanding the mechanistic origin and functional consequences of such variation in Escherichia coli chemotaxis-a well-understood model of signal transduction and behavior. After briefly summarizing the architecture and logic of the chemotaxis system, we discuss determinants of behavior and chemotactic performance of individual cells. Then, we review how cell-to-cell differences in protein abundance map onto differences in individual chemotactic abilities and how phenotypic variability affects the performance of the population. We conclude with open questions to be addressed by future research.

Redox Exfoliation of Layered Transition Metal Dichalcogenides.

Transition metal dichalcogenides (TMDs) have attracted considerable attention in a diverse array of applications due to the breadth of possible property suites relative to other low-dimensional nanomaterials (e.g., graphene, aluminosilicates). Here, we demonstrate an alternative methodology for the exfoliation of bulk crystallites of group V-VII layered TMDs under quiescent, benchtop conditions using mild redox chemistry. Anionic polyoxometalate species generated from edge sites adsorb to the TMD surface and create Coulombic repulsion that drives layer separation without the use of shear forces. This method is generalizable (MS2, MSe2, and MTe2) and effective in preparing high-concentration (>1 mg/mL) dispersions with narrow layer thickness distributions more rapidly and with safer reagents than alternative solution-based approaches. Finally, exfoliation of these TMDs is demonstrated in a range of solvent systems that were previously inaccessible due to large surface energy differences. These characteristics could be beneficial in the preparation of high-quality films and monoliths.

Non-genetic diversity modulates population performance.

Biological functions are typically performed by groups of cells that express predominantly the same genes, yet display a continuum of phenotypes. While it is known how one genotype can generate such non-genetic diversity, it remains unclear how different phenotypes contribute to the performance of biological function at the population level. We developed a microfluidic device to simultaneously measure the phenotype and chemotactic performance of tens of thousands of individual, freely swimming Escherichia coli as they climbed a gradient of attractant. We discovered that spatial structure spontaneously emerged from initially well-mixed wild-type populations due to non-genetic diversity. By manipulating the expression of key chemotaxis proteins, we established a causal relationship between protein expression, non-genetic diversity, and performance that was theoretically predicted. This approach generated a complete phenotype-to-performance map, in which we found a nonlinear regime. We used this map to demonstrate how changing the shape of a phenotypic distribution can have as large of an effect on collective performance as changing the mean phenotype, suggesting that selection could act on both during the process of adaptation.

Defectors Can Create Conditions That Rescue Cooperation.

Cooperation based on the production of costly common goods is observed throughout nature. This is puzzling, as cooperation is vulnerable to exploitation by defectors which enjoy a fitness advantage by consuming the common good without contributing fairly. Depletion of the common good can lead to population collapse and the destruction of cooperation. However, population collapse implies small population size, which, in a structured population, is known to favor cooperation. This happens because small population size increases variability in cooperator frequency across different locations. Since individuals in cooperator-dominated locations (which are most likely cooperators) will grow more than those in defector-dominated locations (which are most likely defectors), cooperators can outgrow defectors globally despite defectors outgrowing cooperators in each location. This raises the possibility that defectors can lead to conditions that sometimes rescue cooperation from defector-induced destruction. We demonstrate multiple mechanisms through which this can occur, using an individual-based approach to model stochastic birth, death, migration, and mutation events. First, during defector-induced population collapse, defectors occasionally go extinct before cooperators by chance, which allows cooperators to grow. Second, empty locations, either preexisting or created by defector-induced population extinction, can favor cooperation because they allow cooperator but not defector migrants to grow. These factors lead to the counterintuitive result that the initial presence of defectors sometimes allows better survival of cooperation compared to when defectors are initially absent. Finally, we find that resource limitation, inducible by defectors, can select for mutations adaptive to resource limitation. When these mutations are initially present at low levels or continuously generated at a moderate rate, they can favor cooperation by further reducing local population size. We predict that in a structured population, small population sizes precipitated by defectors provide a "built-in" mechanism for the persistence of cooperation.

Constructing synthetic microbial communities to explore the ecology and evolution of symbiosis.

Synthetically engineered microbial communities based on model organisms provide a simplified model of their naturally occurring counterparts while still retaining essential features of living organisms. The degree of control afforded by this approach has been critical in understanding how similar types of natural communities might have persisted and evolved. Here, we first discuss important considerations when designing a synthetically engineered system. Then, we describe the steps required to create a two-partner cooperative system based on the yeast Saccharomyces cerevisiae.

Spatial self-organization favors heterotypic cooperation over cheating.

Heterotypic cooperation-two populations exchanging distinct benefits that are costly to produce-is widespread. Cheaters, exploiting benefits while evading contribution, can undermine cooperation. Two mechanisms can stabilize heterotypic cooperation. In 'partner choice', cooperators recognize and choose cooperating over cheating partners; in 'partner fidelity feedback', fitness-feedback from repeated interactions ensures that aiding your partner helps yourself. How might a spatial environment, which facilitates repeated interactions, promote fitness-feedback? We examined this process through mathematical models and engineered Saccharomyces cerevisiae strains incapable of recognition. Here, cooperators and their heterotypic cooperative partners (partners) exchanged distinct essential metabolites. Cheaters exploited partner-produced metabolites without reciprocating, and were competitively superior to cooperators. Despite initially random spatial distributions, cooperators gained more partner neighbors than cheaters did. The less a cheater contributed, the more it was excluded and disfavored. This self-organization, driven by asymmetric fitness effects of cooperators and cheaters on partners during cell growth into open space, achieves assortment. DOI: http://dx.doi.org/10.7554/eLife.00960.001.

Adaptation to a new environment allows cooperators to purge cheaters stochastically.

Cooperation via production of common goods is found in diverse life forms ranging from viruses to social animals. However, natural selection predicts a "tragedy of the commons": Cheaters, benefiting from without producing costly common goods, are more fit than cooperators and should destroy cooperation. In an attempt to discover novel mechanisms of cheater control, we eliminated known ones using a yeast cooperator-cheater system engineered to supply or exploit essential nutrients. Surprisingly, although less fit than cheaters, cooperators quickly dominated a fraction of cocultures. Cooperators isolated from these cocultures were superior to the cheater isolates they had been cocultured with, even though these cheaters were superior to ancestral cooperators. Resequencing and phenotypic analyses revealed that evolved cooperators and cheaters all harbored mutations adaptive to the nutrient-limited cooperative environment, allowing growth at a much lower concentration of nutrient than their ancestors. Even after the initial round of adaptation, evolved cooperators still stochastically dominated cheaters derived from them. We propose the "adaptive race" model: If during adaptation to an environment, the fitness gain of cooperators exceeds that of cheaters by at least the fitness cost of cooperation, the tragedy of the commons can be averted. Although cooperators and cheaters sample from the same pool of adaptive mutations, this symmetry is soon broken: The best cooperators purge cheaters and continue to grow, whereas the best cheaters cause rapid self-extinction. We speculate that adaptation to changing environments may contribute to the persistence of cooperative systems before the appearance of more sophisticated mechanisms of cheater control.

Using artificial systems to explore the ecology and evolution of symbioses.

The web of life is weaved from diverse symbiotic interactions between species. Symbioses vary from antagonistic interactions such as competition and predation to beneficial interactions such as mutualism. What are the bases for the origin and persistence of symbiosis? What affects the ecology and evolution of symbioses? How do symbiotic interactions generate ecological patterns? How do symbiotic partners evolve and coevolve? Many of these questions are difficult to address in natural systems. Artificial systems, from abstract to living, have been constructed to capture essential features of natural symbioses and to address these key questions. With reduced complexity and increased controllability, artificial systems can serve as useful models for natural systems. We review how artificial systems have contributed to our understanding of symbioses.

A rapid and general assay for monitoring endogenous gene modification.

The development of zinc finger nucleases for targeted gene modification can benefit from rapid functional assays that directly quantify activity at the endogenous target. Here we describe a simple procedure for quantifying mutations that result from DNA double-strand break repair via non-homologous end joining. The assay is based on the ability of the Surveyor nuclease to selectively cleave distorted duplex DNA formed via cross-annealing of mutated and wild-type sequence.

Establishment of HIV-1 resistance in CD4+ T cells by genome editing using zinc-finger nucleases.

Homozygosity for the naturally occurring Delta32 deletion in the HIV co-receptor CCR5 confers resistance to HIV-1 infection. We generated an HIV-resistant genotype de novo using engineered zinc-finger nucleases (ZFNs) to disrupt endogenous CCR5. Transient expression of CCR5 ZFNs permanently and specifically disrupted approximately 50% of CCR5 alleles in a pool of primary human CD4(+) T cells. Genetic disruption of CCR5 provided robust, stable and heritable protection against HIV-1 infection in vitro and in vivo in a NOG model of HIV infection. HIV-1-infected mice engrafted with ZFN-modified CD4(+) T cells had lower viral loads and higher CD4(+) T-cell counts than mice engrafted with wild-type CD4(+) T cells, consistent with the potential to reconstitute immune function in individuals with HIV/AIDS by maintenance of an HIV-resistant CD4(+) T-cell population. Thus adoptive transfer of ex vivo expanded CCR5 ZFN-modified autologous CD4(+) T cells in HIV patients is an attractive approach for the treatment of HIV-1 infection.

Targeted gene knockout in mammalian cells by using engineered zinc-finger nucleases.

Gene knockout is the most powerful tool for determining gene function or permanently modifying the phenotypic characteristics of a cell. Existing methods for gene disruption are limited by their efficiency, time to completion, and/or the potential for confounding off-target effects. Here, we demonstrate a rapid single-step approach to targeted gene knockout in mammalian cells, using engineered zinc-finger nucleases (ZFNs). ZFNs can be designed to target a chosen locus with high specificity. Upon transient expression of these nucleases the target gene is first cleaved by the ZFNs and then repaired by a natural-but imperfect-DNA repair process, nonhomologous end joining. This often results in the generation of mutant (null) alleles. As proof of concept for this approach we designed ZFNs to target the dihydrofolate reductase (DHFR) gene in a Chinese hamster ovary (CHO) cell line. We observed biallelic gene disruption at frequencies >1%, thus obviating the need for selection markers. Three new genetically distinct DHFR(-/-) cell lines were generated. Each new line exhibited growth and functional properties consistent with the specific knockout of the DHFR gene. Importantly, target gene disruption is complete within 2-3 days of transient ZFN delivery, thus enabling the isolation of the resultant DHFR(-/-) cell lines within 1 month. These data demonstrate further the utility of ZFNs for rapid mammalian cell line engineering and establish a new method for gene knockout with application to reverse genetics, functional genomics, drug discovery, and therapeutic recombinant protein production.

An improved zinc-finger nuclease architecture for highly specific genome editing.

Genome editing driven by zinc-finger nucleases (ZFNs) yields high gene-modification efficiencies (>10%) by introducing a recombinogenic double-strand break into the targeted gene. The cleavage event is induced using two custom-designed ZFNs that heterodimerize upon binding DNA to form a catalytically active nuclease complex. Using the current ZFN architecture, however, cleavage-competent homodimers may also form that can limit safety or efficacy via off-target cleavage. Here we develop an improved ZFN architecture that eliminates this problem. Using structure-based design, we engineer two variant ZFNs that efficiently cleave DNA only when paired as a heterodimer. These ZFNs modify a native endogenous locus as efficiently as the parental architecture, but with a >40-fold reduction in homodimer function and much lower levels of genome-wide cleavage. This architecture provides a general means for improving the specificity of ZFNs as gene modification reagents.