Automated assembly scaffolding elevates a new tomato system for high-throughput genome editing

Advancing crop genomics requires efficient genetic systems enabled by high-quality personalized genome assemblies. Here, we introduce RagTag, a toolset for automating assembly scaffolding and patching, and we establish chromosome-scale reference genomes for the widely used tomato genotype M82 along with Sweet-100, a rapid-cycling genotype that we developed to accelerate functional genomics and genome editing. This work outlines strategies to rapidly expand genetic systems and genomic resources in other plant species.

The copper resistome of group B Streptococcus reveals insight into the genetic basis of cellular survival during metal ion stress

In bacteria, copper (Cu) can support metabolic processes as an enzymatic cofactor but can also cause cell damage if present in excess, leading to intoxication. In group B Streptococcus (GBS) a system for control of Cu efflux based on the canonical cop operon supports survival during Cu stress. In some other bacteria, genetic systems additional to the cop operon are engaged during Cu stress and also contribute to Cu management. Here, we examined genetic systems beyond the cop operon in GBS for regions that contribute to survival of GBS in Cu stress using a forward genetic screen and probe of the entire bacterial genome. A high-density mutant library, generated using pGh9-ISS1, was used to expose GBS to Cu stress and compared to non-exposed controls en masse. Nine genes were identified as essential for GBS survival in Cu stress, whereas five genes constrained GBS growth in Cu stress. The genes encode varied factors including enzymes for metabolism, cell wall synthesis, transporters and global transcriptional regulators. Targeted mutation of the genes validated their roles in GBS resistance to Cu stress. Notably, several genes, including stp1, yceG, plyB and rfaB were also essential for resistance to Zn stress. Excepting copA, the genes identified are new to the area of bacterial metal ion intoxication. We conclude that a discrete and limited suite of genes beyond the cop operon in GBS contribute to a repertoire of mechanisms used to survive Cu stress in vitro and achieve cellular homeostasis.

Automated Model-Predictive Design of Synthetic Promoters to Control Transcriptional Profiles in Bacteria

Transcription rates are regulated by the interactions between RNA polymerase, sigma factor, and promoter DNA sequences in bacteria. However, it remains unclear how non-canonical sequence motifs collectively control transcription rates. Here, we combined massively parallel assays, biophysics, and machine learning to develop a 346-parameter model that predicts site-specific transcription initiation rates for any σ70 promoter sequence, validated across 17396 bacterial promoters with diverse sequences. We applied the model to predict genetic context effects, design σ70 promoters with desired transcription rates, and identify undesired promoters inside engineered genetic systems. The model provides a biophysical basis for understanding gene regulation in natural genetic systems and precise transcriptional control for engineering synthetic genetic systems.

Large-scale identification of viral quorum sensing systems reveal convergent evolution of density-dependent sporulation-hijacking in bacteriophages

Quorum sensing systems (QSSs) are genetic systems supporting cell-cell or bacteriophage-bacteriophage communication. By regulating behavioral switches as a function of the encoding population density, QSSs shape the social dynamics of microbial communities. However, their diversity is tremendously overlooked in bacteriophages, which implies that many density-dependent behaviors likely remains to be discovered in these viruses. Here, we developed a signature-based computational method to identify novel peptide-based RRNPP QSSs in gram-positive bacteria (e.g. Firmicutes) and their mobile genetic elements. The large-scale application of this method against available genomes of Firmicutes and bacteriophages revealed 2708 candidate RRNPP-type QSSs, including 382 found in (pro)phages. These 382 viral candidate QSSs are classified into 25 different groups of homologs, of which 22 were never described before in bacteriophages. Remarkably, genomic context analyses suggest that candidate viral QSSs from 6 different families dynamically manipulate the host biology. Specifically, many viral candidate QSSs are predicted to regulate, in a density-dependent manner, adjacent (pro)phage-encoded regulator genes whose bacterial homologs are key regulators of the sporulation initiation pathway (either Rap, Spo0E, or AbrB). Consistently, we found evidence from public data that certain of our candidate (pro)phage-encoded QSSs dynamically manipulate the timing of sporulation of the bacterial host. These findings challenge the current paradigm assuming that bacteria decide to sporulate in adverse situation. Indeed, our survey highlights that bacteriophages have evolved, multiple times, genetic systems that dynamically influence this decision to their advantage, making sporulation a survival mechanism of last resort for phage-host collectives.

The finding and researching algorithm for potentially oscillating enzymatic systems

Many processes in living organisms are subject to periodic oscillations at different hierarchical levels of their organization: from molecular-genetic to population and ecological. Oscillatory processes are responsible for cell cycles in both prokaryotes and eukaryotes, for circadian rhythms, for synchronous coupling of respiration with cardiac contractions, etc. Fluctuations in the numbers of organisms in natural populations can be caused by the populations’ own properties, their age structure, and ecological relationships with other species. Along with experimental approaches, mathematical and computer modeling is widely used to study oscillating biological systems. This paper presents classical mathematical models that describe oscillatory behavior in biological systems. Methods for the search for oscillatory molecular-genetic systems are presented by the example of their special case – oscillatory enzymatic systems. Factors influencing the cyclic dynamics in living systems, typical not only of the molecular-genetic level, but of higher levels of organization as well, are considered. Application of different ways to describe gene networks for modeling oscillatory molecular-genetic systems is considered, where the most important factor for the emergence of cyclic behavior is the presence of feedback. Techniques for finding potentially oscillatory enzymatic systems are presented. Using the method described in the article, we present and analyze, in a step-by-step manner, first the structural models (graphs) of gene networks and then the reconstruction of the mathematical models and computational experiments with them. Structural models are ideally suited for the tasks of an automatic search for potential oscillating contours (linked subgraphs), whose structure can correspond to the mathematical model of the molecular-genetic system that demonstrates oscillatory behavior in dynamics. At the same time, it is the numerical study of mathematical models for the selected contours that makes it possible to confirm the presence of stable limit cycles in them. As an example of application of the technology, a network of 300 metabolic reactions of the bacterium Escherichia coli was analyzed using mathematical and computer modeling tools. In particular, oscillatory behavior was shown for a loop whose reactions are part of the tryptophan biosynthesis pathway.

Immunogenetic characteristics of sires Simmental and Red-and-White breeds in Stud bull farm «Barnaulskoe»

The purpose of the research was to study the frequency of erythrocyte antigens of 9 genetic systems, the number of genotypes and the frequency of alleles in the F-V system in sires Simmental and Red-and-White breeds, as well as to establish the index of genetic similarity between them.The characteristics of 106 sires Simmental and 103 Red-and-White breeds in OJSC “Barnaulskoe” Stud bull farm have been given according to the frequency of erythrocyte antigens of 9 genetic systems. 53 antiserums have been used in the tests. The high occurrence of erythrocyte antigens A2 (system A), B2, G2, O1, Y2, G’, O’, and Q’ (system B), C2, E, W, X2 (system C), S1, H’ (system S), and Z (system Z) has been found in the sires of both breeds and ranged from 0,204 (O’) to 0,825 (X2) in Red-and-White bulls. The maximum frequency of the F antigen was and it was 0,874 in Red-and-White and 0,906 in Simmental bulls. On the contrary, the occurrence of blood factors B1, I1, I2, O2, P1, P2, Q, T1, T2, I’, D’, J2’, K’, P1’, P2’, Y’, B”, G”, R1, J, H, U and U’ was signifi cantly lower and amounted to 0–0,107 in Red-and-White sires and 0–0,094 in Simmental sires. Only 42 erythrocyte antigens have been detected in Red-and-White bulls using 53 antiserums, and 44 antigens have been detected in Simmental bulls. The index of genetic similarity between Red-and-White and Simmental sires calculated according to A. S. Serebrovsky was quite high and amounted to 0,8765, which is understandable because the maternal breed when breeding Red-and-White breed was Simmental breed. The number of genotypes and the frequency of alleles in the F-V genetic system also revealed a great similarity between these breeds, a significant difference has been found only in the number of heterozygous animals.

Stability and Robustness of Unbalanced Genetic Toggle Switches in the Presence of Scarce Resources

While the vision of synthetic biology is to create complex genetic systems in a rational fashion, system-level behaviors are often perplexing due to the context-dependent dynamics of modules. One major source of context-dependence emerges due to the limited availability of shared resources, coupling the behavior of disconnected components. Motivated by the ubiquitous role of toggle switches in genetic circuits ranging from controlling cell fate differentiation to optimizing cellular performance, here we reveal how their fundamental dynamic properties are affected by competition for scarce resources. Combining a mechanistic model with nullcline-based stability analysis and potential landscape-based robustness analysis, we uncover not only the detrimental impacts of resource competition, but also how the unbalancedness of the switch further exacerbates them. While in general both of these factors undermine the performance of the switch (by pushing the dynamics toward monostability and increased sensitivity to noise), we also demonstrate that some of the unwanted effects can be alleviated by strategically optimized resource competition. Our results provide explicit guidelines for the context-aware rational design of toggle switches to mitigate our reliance on lengthy and expensive trial-and-error processes, and can be seamlessly integrated into the computer-aided synthesis of complex genetic systems.