Elucidating human gut microbiota interactions that robustly inhibit diverse Clostridioides difficile strains across different nutrient landscapes.

The human gut pathogen Clostridioides difficile displays extreme genetic variability and confronts a changeable nutrient landscape in the gut. We mapped gut microbiota inter-species interactions impacting the growth and toxin production of diverse C. difficile strains in different nutrient environments. Although negative interactions impacting C. difficile are prevalent in environments promoting resource competition, they are sparse in an environment containing C. difficile-preferred carbohydrates. C. difficile strains display differences in interactions with Clostridium scindens and the ability to compete for proline. C. difficile toxin production displays substantial community-context dependent variation and does not trend with growth-mediated inter-species interactions. C. difficile shows substantial differences in transcriptional profiles in the presence of the closely related species C. hiranonis or C. scindens. In co-culture with C. hiranonis, C. difficile exhibits massive alterations in metabolism and other cellular processes, consistent with their high metabolic overlap. Further, Clostridium hiranonis inhibits the growth and toxin production of diverse C. difficile strains across different nutrient environments and ameliorates the disease severity of a C. difficile challenge in a murine model. In sum, strain-level variability and nutrient environments are major variables shaping gut microbiota interactions with C. difficile.

Single-cell analysis of multiple invertible promoters reveals differential inversion rates as a strong determinant of bacterial population heterogeneity.

Population heterogeneity can promote bacterial fitness in response to unpredictable environmental conditions. A major mechanism of phenotypic variability in the human gut symbiont Bacteroides spp. involves the inversion of promoters that drive the expression of capsular polysaccharides, which determine the architecture of the cell surface. High-throughput single-cell sequencing reveals substantial population heterogeneity generated through combinatorial promoter inversion regulated by a broadly conserved serine recombinase. Exploiting control over population diversification, we show that populations with different initial compositions converge to a similar composition over time. Combining our data with stochastic computational modeling, we demonstrate that the differential rates of promoter inversion are a major mechanism shaping population dynamics. More broadly, our approach could be used to interrogate single-cell combinatorial phase variable states of diverse microbes including bacterial pathogens.

Carbohydrate complexity limits microbial growth and reduces the sensitivity of human gut communities to perturbations.

Dietary fibre impacts the growth dynamics of human gut microbiota, yet we lack a detailed and quantitative understanding of how these nutrients shape microbial interaction networks and responses to perturbations. By building human gut communities coupled with computational modelling, we dissect the effects of fibres that vary in chemical complexity and each of their constituent sugars on community assembly and response to perturbations. We demonstrate that the degree of chemical complexity across different fibres limits microbial growth and the number of species that can utilize these nutrients. The prevalence of negative interspecies interactions is reduced in the presence of fibres compared with their constituent sugars. Carbohydrate chemical complexity enhances the reproducibility of community assembly and resistance of the community to invasion. We demonstrate that maximizing or minimizing carbohydrate competition between resident and invader species enhances resistance to invasion. In sum, the quantitative effects of carbohydrate chemical complexity on microbial interaction networks could be exploited to inform dietary and bacterial interventions to modulate community resistance to perturbations.

Robust and tunable signal processing in mammalian cells via engineered covalent modification cycles.

Engineered signaling networks can impart cells with new functionalities useful for directing differentiation and actuating cellular therapies. For such applications, the engineered networks must be tunable, precisely regulate target gene expression, and be robust to perturbations within the complex context of mammalian cells. Here, we use bacterial two-component signaling proteins to develop synthetic phosphoregulation devices that exhibit these properties in mammalian cells. First, we engineer a synthetic covalent modification cycle based on kinase and phosphatase proteins derived from the bifunctional histidine kinase EnvZ, enabling analog tuning of gene expression via its response regulator OmpR. By regulating phosphatase expression with endogenous miRNAs, we demonstrate cell-type specific signaling responses and a new strategy for accurate cell type classification. Finally, we implement a tunable negative feedback controller via a small molecule-stabilized phosphatase, reducing output expression variance and mitigating the context-dependent effects of off-target regulation and resource competition. Our work lays the foundation for establishing tunable, precise, and robust control over cell behavior with synthetic signaling networks.

Polysaccharide utilization loci in Bacteroides determine population fitness and community-level interactions.

Polysaccharide utilization loci (PULs) are co-regulated bacterial genes that sense nutrients and enable glycan digestion. Human gut microbiome members, notably Bacteroides, contain numerous PULs that enable glycan utilization and shape ecological dynamics. To investigate the role of PULs on fitness and inter-species interactions, we develop a CRISPR-based genome editing tool to study 23 PULs in Bacteroides uniformis (BU). BU PULs show distinct glycan-degrading functions and transcriptional coordination that enables the population to adapt upon loss of other PULs. Exploiting a BU mutant barcoding strategy, we demonstrate that in vitro fitness and BU colonization in the murine gut are enhanced by deletion of specific PULs and modulated by glycan availability. PULs mediate glycan-dependent interactions with butyrate producers that depend on the degradation mechanism and glycan utilization ability of the butyrate producer. Thus, PULs determine community dynamics and butyrate production and provide a selective advantage or disadvantage depending on the nutritional landscape.

Negative interactions determine Clostridioides difficile growth in synthetic human gut communities.

Understanding the principles of colonization resistance of the gut microbiome to the pathogen Clostridioides difficile will enable the design of defined bacterial therapeutics. We investigate the ecological principles of community resistance to C. difficile using a synthetic human gut microbiome. Using a dynamic computational model, we demonstrate that C. difficile receives the largest number and magnitude of incoming negative interactions. Our results show that C. difficile is in a unique class of species that display a strong negative dependence between growth and species richness. We identify molecular mechanisms of inhibition including acidification of the environment and competition over resources. We demonstrate that Clostridium hiranonis strongly inhibits C. difficile partially via resource competition. Increasing the initial density of C. difficile can increase its abundance in the assembled community, but community context determines the maximum achievable C. difficile abundance. Our work suggests that the C. difficile inhibitory potential of defined bacterial therapeutics can be optimized by designing communities featuring a combination of mechanisms including species richness, environment acidification, and resource competition.

Towards a deeper understanding of microbial communities: integrating experimental data with dynamic models.

Microbial communities and their functions are shaped by complex networks of interactions among microbes and with their environment. While the critical roles microbial communities play in numerous environments have become increasingly appreciated, we have a very limited understanding of their interactions and how these interactions combine to generate community-level behaviors. This knowledge gap hinders our ability to predict community responses to perturbations and to design interventions that manipulate these communities to our benefit. Dynamic models are promising tools to address these questions. We review existing modeling techniques to construct dynamic models of microbial communities at different scales and suggest ways to leverage multiple types of models and data to facilitate our understanding and engineering of microbial communities.

dCas9 regulator to neutralize competition in CRISPRi circuits.

CRISPRi-mediated gene regulation allows simultaneous control of many genes. However, highly specific sgRNA-promoter binding is, alone, insufficient to achieve independent transcriptional regulation of multiple targets. Indeed, due to competition for dCas9, the repression ability of one sgRNA changes significantly when another sgRNA becomes expressed. To solve this problem and decouple sgRNA-mediated regulatory paths, we create a dCas9 concentration regulator that implements negative feedback on dCas9 level. This allows any sgRNA to maintain an approximately constant dose-response curve, independent of other sgRNAs. We demonstrate the regulator performance on both single-stage and layered CRISPRi-based genetic circuits, zeroing competition effects of up to 15-fold changes in circuit I/O response encountered without the dCas9 regulator. The dCas9 regulator decouples sgRNA-mediated regulatory paths, enabling concurrent and independent regulation of multiple genes. This allows predictable composition of CRISPRi-based genetic modules, which is essential in the design of larger scale synthetic genetic circuits.

An endoribonuclease-based feedforward controller for decoupling resource-limited genetic modules in mammalian cells.

Synthetic biology has the potential to bring forth advanced genetic devices for applications in healthcare and biotechnology. However, accurately predicting the behavior of engineered genetic devices remains difficult due to lack of modularity, wherein a device's output does not depend only on its intended inputs but also on its context. One contributor to lack of modularity is loading of transcriptional and translational resources, which can induce coupling among otherwise independently-regulated genes. Here, we quantify the effects of resource loading in engineered mammalian genetic systems and develop an endoribonuclease-based feedforward controller that can adapt the expression level of a gene of interest to significant resource loading in mammalian cells. Near-perfect adaptation to resource loads is facilitated by high production and catalytic rates of the endoribonuclease. Our design is portable across cell lines and enables predictable tuning of controller function. Ultimately, our controller is a general-purpose device for predictable, robust, and context-independent control of gene expression.

A quasi-integral controller for adaptation of genetic modules to variable ribosome demand.

The behavior of genetic circuits is often poorly predictable. A gene's expression level is not only determined by the intended regulators, but also affected by changes in ribosome availability imparted by expression of other genes. Here we design a quasi-integral biomolecular feedback controller that enables the expression level of any gene of interest (GOI) to adapt to changes in available ribosomes. The feedback is implemented through a synthetic small RNA (sRNA) that silences the GOI's mRNA, and uses orthogonal extracytoplasmic function (ECF) sigma factor to sense the GOI's translation and to actuate sRNA transcription. Without the controller, the expression level of the GOI is reduced by 50% when a resource competitor is activated. With the controller, by contrast, gene expression level is practically unaffected by the competitor. This feedback controller allows adaptation of genetic modules to variable ribosome demand and thus aids modular construction of complicated circuits.

Realizing 'integral control' in living cells: how to overcome leaky integration due to dilution?

A major problem in the design of synthetic genetic circuits is robustness to perturbations and uncertainty. Because of this, there have been significant efforts in recent years in finding approaches to implement integral control in genetic circuits. Integral controllers have the unique ability to make the output of a process adapt perfectly to disturbances. However, implementing an integral controller is challenging in living cells. This is because a key aspect of any integral controller is a 'memory' element that stores the accumulation (integral) of the error between the output and its desired set-point. The ability to realize such a memory element in living cells is fundamentally challenged by the fact that all biomolecules dilute as cells grow, resulting in a 'leaky' memory that gradually fades away. As a consequence, the adaptation property is lost. Here, we propose a general principle for designing integral controllers such that the performance is practically unaffected by dilution. In particular, we mathematically prove that if the reactions implementing the integral controller are all much faster than dilution, then the adaptation error due to integration leakiness becomes negligible. We exemplify this design principle with two synthetic genetic circuits aimed at reaching adaptation of gene expression to fluctuations in cellular resources. Our results provide concrete guidance on the biomolecular processes that are most appropriate for implementing integral controllers in living cells.

Resource Competition Shapes the Response of Genetic Circuits.

A common approach to design genetic circuits is to compose gene expression cassettes together. While appealing, this modular approach is challenged by the fact that expression of each gene depends on the availability of transcriptional/translational resources, which is in turn determined by the presence of other genes in the circuit. This raises the question of how competition for resources by different genes affects a circuit's behavior. Here, we create a library of genetic activation cascades in E. coli bacteria, where we explicitly tune the resource demand by each gene. We develop a general Hill-function-based model that incorporates resource competition effects through resource demand coefficients. These coefficients lead to nonregulatory interactions among genes that reshape the circuit's behavior. For the activation cascade, such interactions result in surprising biphasic or monotonically decreasing responses. Finally, we use resource demand coefficients to guide the choice of ribosome binding site and DNA copy number to restore the cascade's intended monotonically increasing response. Our results demonstrate how unintended circuit's behavior arises from resource competition and provide a model-guided methodology to minimize the resulting effects.

A Blueprint for a Synthetic Genetic Feedback Controller to Reprogram Cell Fate.

To artificially reprogram cell fate, experimentalists manipulate the gene regulatory networks (GRNs) that maintain a cell's phenotype. In practice, reprogramming is often performed by constant overexpression of specific transcription factors (TFs). This process can be unreliable and inefficient. Here, we address this problem by introducing a new approach to reprogramming based on mathematical analysis. We demonstrate that reprogramming GRNs using constant overexpression may not succeed in general. Instead, we propose an alternative reprogramming strategy: a synthetic genetic feedback controller that dynamically steers the concentration of a GRN's key TFs to any desired value. The controller works by adjusting TF expression based on the discrepancy between desired and actual TF concentrations. Theory predicts that this reprogramming strategy is guaranteed to succeed, and its performance is independent of the GRN's structure and parameters, provided that feedback gain is sufficiently high. As a case study, we apply the controller to a model of induced pluripotency in stem cells.

Control theory meets synthetic biology.

The past several years have witnessed an increased presence of control theoretic concepts in synthetic biology. This review presents an organized summary of how these control design concepts have been applied to tackle a variety of problems faced when building synthetic biomolecular circuits in living cells. In particular, we describe success stories that demonstrate how simple or more elaborate control design methods can be used to make the behaviour of synthetic genetic circuits within a single cell or across a cell population more reliable, predictable and robust to perturbations. The description especially highlights technical challenges that uniquely arise from the need to implement control designs within a new hardware setting, along with implemented or proposed solutions. Some engineering solutions employing complex feedback control schemes are also described, which, however, still require a deeper theoretical analysis of stability, performance and robustness properties. Overall, this paper should help synthetic biologists become familiar with feedback control concepts as they can be used in their application area. At the same time, it should provide some domain knowledge to control theorists who wish to enter the rising and exciting field of synthetic biology.

Efficacy of artemether and artesunate in mice infected with praziquantel non-susceptible isolate of Schistosoma japonicum.

Praziquantel is currently the only drug of choice for the treatment of human Schistosoma japonicum infections, and praziquantel-based chemotherapy has been proved to be generally effective to control the morbidity and reduce the prevalence and intensity of S. japonicum infections. However, the potential emergence of praziquantel resistance in S. japonicum seriously threatens the elimination of this neglected tropical disease in China. The purpose of this study was designed, in mouse animals, to evaluate the in vivo efficacy of artemether and artesunate against praziquantel non-susceptible S. japonicum. Mice infected with a praziquantel non-susceptible isolate and a praziquantel-susceptible isolate of S. japonicum were treated with artemether and artesunate at a single oral dose of 300 mg/kg given once on each of days 7-8 and 35-36 post-infection to assess the efficacy against juvenile and adult worms. Administration with artemether and artesunate at a single oral dose of 300 mg/kg on each of days 7-8 post-infection resulted in total worm burden reductions of 72.8 and 73.5% in mice infected with praziquantel-susceptible S. japonicum, and 77.9 and 74.1% in mice infected with the non-susceptible isolate (both P values >0.05), while the same treatments given on days 35-36 post-infection reduced total worm burdens by 71.4 and 69.6% in mice infected with the susceptible isolate, and 75.3 and 69.6% in mice infected with the non-susceptible parasite (both P values >0.05). It is concluded that there is no evidence for reduced susceptibility of artemether and artesunate in praziquantel non-susceptible S. japonicum.

[Bibliometric analysis of literature regarding integrated schistosomiasis control strategy with emphasis on infectious source control].

OBJECTIVE: To evaluate the outcomes of implementation of integrated schistosomiasis control strategy with emphasis on infectious source control using a bibliometric method. METHODS: The literature pertaining to integrated schistosomiasis control strategy with emphasis on infectious source control was retrieved from CNKI, Wanfangdata, VIP, PubMed, Web of Science, BIOSIS and Google Scholar, and a bibliometric analysis of literature captured was performed. RESULTS: During the period from January 1, 2004 through September 30, 2014, a total of 94 publications regarding integrated schistosomiasis control strategy with emphasis on infectious source control were captured, including 78 Chinese articles (82.98%) and 16 English papers (17.02%). The Chinese literature was published in 21 national journals, and Chinese Journal of Schistosomiasis Control had the largest number of publications, consisting of 37.23% of total publications; 16 English papers were published in 12 international journals, and PLoS Neglected Tropical Diseases had the largest number of publications (3 publications). There were 37 affiliations publishing these 94 articles, and National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention (16 publications), Anhui Institute of Schistosomiasis Control (12 publications) and Hunan Institute of Schistosomiasis Control (9 publications) ranked top three affiliations in number of publications. A total of 157 persons were co-authored in these 94 publications, and Wang, Zhou and Zhang ranked top 3 authors in number of publications. CONCLUSION: The integrated schistosomiasis control strategy with emphasis on infectious source control has been widely implemented in China, and the achievements obtained from the implementation of this strategy should be summarized and transmitted internationally.

In vivo activity of dihydroartemisinin against Schistosoma mansoni schistosomula in mice.

Dihydroartemisinin, an anti-malarial agent, has been shown to exhibit activity against Schistosoma japonicum and S. mansoni. The purpose of the present study was to investigate the in vivo activity of dihydroartemisinin against juvenile S. mansoni and the changes to the genital system among worms surviving drug treatment. Mice were infected with 200 S. mansoni cercariae each and randomly assigned to groups. Dihydroartemisinin at a single oral dose of 300 mg/kg was given to mice on Days 14 or 16, 18, 20, 21, 22, 24, 26 or 28 post-infection, to assess the efficacy of dihydroartemisinin against juvenile S. mansoni. Mice were treated with dihydroartemisinin using various protocols with the total drug dose of 900 mg/kg, to investigate the efficacy of dihydroartemisinin against the schistosomula of S. mansoni. In addition, changes to the genital system among worms surviving dihydroartemisinin treatment, were recorded. An oral dose of dihydroartemisinin of 300 mg/kg was given to mice on Days 14, 16, 18, 20, 21, 22, 24, 26 or 28 days post-infection; this resulted in a 65.0-82.4% reduction in total worm burden and a 70.9-83.0% female worm burden. Better results were seen when treatment was given 20-24 days post-infection. Administration of multiple-dose and low-oral-dose dihydroarteminisinin (at doses of 90, 180, 300 and 450 mg/kg) at different times, reduced total worm burdens by 88.7-99.1% and female worm burdens by 93.2-99.5%. The egg tubercles in mice livers were significantly reduced following treatment; in some mice no egg tubercles were found. These findings indicate dihydroartemisinin exhibits high in vivo activity against the schistosomula of S. mansoni. It causes damage to the genital system of worms, influences the development of of S. mansoni worms, reduces the oviposition of surviving worms and enhances the formation of granulomas around tissue-trapped eggs, thereby reducing damage to the infected mammalian host.