Debugging and consolidating multiple synthetic chromosomes reveals combinatorial genetic interactions.

The Sc2.0 project is building a eukaryotic synthetic genome from scratch. A major milestone has been achieved with all individual Sc2.0 chromosomes assembled. Here, we describe the consolidation of multiple synthetic chromosomes using advanced endoreduplication intercrossing with tRNA expression cassettes to generate a strain with 6.5 synthetic chromosomes. The 3D chromosome organization and transcript isoform profiles were evaluated using Hi-C and long-read direct RNA sequencing. We developed CRISPR Directed Biallelic URA3-assisted Genome Scan, or "CRISPR D-BUGS," to map phenotypic variants caused by specific designer modifications, known as "bugs." We first fine-mapped a bug in synthetic chromosome II (synII) and then discovered a combinatorial interaction associated with synIII and synX, revealing an unexpected genetic interaction that links transcriptional regulation, inositol metabolism, and tRNASerCGA abundance. Finally, to expedite consolidation, we employed chromosome substitution to incorporate the largest chromosome (synIV), thereby consolidating >50% of the Sc2.0 genome in one strain.

Developing a genetic testing panel for evaluation of morbidities in kidney transplant recipients.

Cardiovascular disease, infection, malignancy, and thromboembolism are major causes of morbidity and mortality in kidney transplant recipients (KTR). Prospectively identifying monogenic conditions associated with post-transplant complications may enable personalized management. Therefore, we developed a transplant morbidity panel (355 genes) associated with major post-transplant complications including cardiometabolic disorders, immunodeficiency, malignancy, and thrombophilia. This gene panel was then evaluated using exome sequencing data from 1590 KTR. Additionally, genes associated with monogenic kidney and genitourinary disorders along with American College of Medical Genetics (ACMG) secondary findings v3.2 were annotated. Altogether, diagnostic variants in 37 genes associated with Mendelian kidney and genitourinary disorders were detected in 9.9% (158/1590) of KTR; 25.9% (41/158) had not been clinically diagnosed. Moreover, the transplant morbidity gene panel detected diagnostic variants for 56 monogenic disorders in 9.1% KTRs (144/1590). Cardiovascular disease, malignancy, immunodeficiency, and thrombophilia variants were detected in 5.1% (81), 2.1% (34), 1.8% (29) and 0.2% (3) among 1590 KTRs, respectively. Concordant phenotypes were present in half of these cases. Reviewing implications for transplant care, these genetic findings would have allowed physicians to set specific risk factor targets in 6.3% (9/144), arrange intensive surveillance in 97.2% (140/144), utilize preventive measures in 13.2% (19/144), guide disease-specific therapy in 63.9% (92/144), initiate specialty referral in 90.3% (130/144) and alter immunosuppression in 56.9% (82/144). Thus, beyond diagnostic testing for kidney disorders, sequence annotation identified monogenic disorders associated with common post-transplant complications in 9.1% of KTR, with important clinical implications. Incorporating genetic diagnostics for transplant morbidities would enable personalized management in pre- and post-transplant care.

Assisting the analysis of insertions and deletions using regional allele frequencies.

Accurate estimation of population allele frequency (AF) is crucial for gene discovery and genetic diagnostics. However, determining AF for frameshift-inducing small insertions and deletions (indels) faces challenges due to discrepancies in mapping and variant calling methods. Here, we propose an innovative approach to assess indel AF. We developed CRAFTS-indels (Calculating Regional Allele Frequency Targeting Small indels), an algorithm that combines AF of distinct indels within a given region and provides "regional AF" (rAF). We tested and validated CRAFTS-indels using three independent datasets: gnomAD v2 (n=125,748 samples), an internal dataset (IGM; n=39,367), and the UK BioBank (UKBB; n=469,835). By comparing rAF against standard AF, we identified rare indels with rAF exceeding standard AF (sAF≤10-4 and rAF>10-4) as "rAF-hi" indels. Notably, a high percentage of rare indels were "rAF-hi", with a higher proportion in gnomAD v2 (11-20%) and IGM (11-22%) compared to the UKBB (5-9% depending on the CRAFTS-indels' parameters). Analysis of the overlap of regions based on their rAF with low complexity regions and with ClinVar classification supported the pertinence of rAF. Using the internal dataset, we illustrated the utility of CRAFTS-indel in the analysis of de novo variants and the potential negative impact of rAF-hi indels in gene discovery. In summary, annotation of indels with cohort specific rAF can be used to handle some of the limitations of current annotation pipelines and facilitate detection of novel gene disease associations. CRAFTS-indels offers a user-friendly approach to providing rAF annotation. It can be integrated into public databases such as gnomAD, UKBB and used by ClinVar to revise indel classifications.

Covalent Immobilization of N-Acetylcysteine on a Polyvinyl Chloride Substrate Prevents Bacterial Adhesion and Biofilm Formation.

Biofilm formation and antimicrobial resistance at surgical implant sites result in high morbidity and mortality. Identifying novel molecules that inhibit biofilm formation to coat surgical biomaterials is essential. One such compound is N-acetylcysteine (NAC), a potent antioxidant precursor for glutathione, necessary in mammalian cells and known to disrupt/prevent biofilms. In this study, NAC was covalently immobilized onto functionalized polyvinyl chloride surfaces using plasma immersion ion implantation (PIII) treatment that achieves covalent binding without the need for linker groups. NAC immobilization was characterized using water contact angles, Fourier-transform infrared, and X-ray photoelectron spectroscopy techniques. Bacterial viability and biofilm formation on NAC surfaces were assessed using resazurin assays, phase contrast microscopy, and colony counting experiments. Effect of NAC on bacterial polysaccharide production and DNA cleaving was investigated using the phenol-sulfuric acid method and the Qubit fluorometer. Surface thermodynamics between the NAC coating and bacterial cells were measured using the Lewis acid-base method. Surface characterization techniques demonstrated superficial changes after PIII treatment and subsequent covalent NAC immobilization. NAC-coated surfaces significantly reduced biofilm viability and the presence of Gram-negative and Gram-positive bacteria. NAC also decreased polysaccharide production and degraded DNA. This led to unfavorable conditions for biofilm formation on NAC-coated surfaces, as demonstrated by surface thermodynamic analysis. NAC-coated surfaces showed no cytotoxicity to human fibroblast cells. This study has successfully utilized NAC as an antibiofilm coating, which may pave the way for improved prophylactic coatings on medical implant devices in the future.

Transition Towards Antibiotic Hybrid Vehicles: The Next Generation Antibacterials.

Antibiotic resistance is a growing global health problem when the discovery and development of novel antibiotics are diminishing. Various strategies have been proposed to address the problem of growing antibacterial resistance. One such strategy is the development of hybrid antibiotics. These therapeutic systems have been designed for two or more pharmacophores of known antimicrobial agents. This review highlights the latest development of antibiotic hybrids comprising two antibiotics (cleavable and non-cleavable) and combinations of biocidal and novel compounds to treat bacterial infections. The approach of dual-acting hybrid compounds has a promising future in overcoming drug resistance in bacterial pathogens.

An "optimal" spawning algorithm for adaptive basis set expansion in nonadiabatic dynamics.

The full multiple spawning (FMS) method has been developed to simulate quantum dynamics in the multistate electronic problem. In FMS, the nuclear wave function is represented in a basis of coupled, frozen Gaussians, and a "spawning" procedure prescribes a means of adaptively increasing the size of this basis in order to capture population transfer between electronic states. Herein we detail a new algorithm for specifying the initial conditions of newly spawned basis functions that minimizes the number of spawned basis functions needed for convergence. "Optimally" spawned basis functions are placed to maximize the coupling between parent and child trajectories at the point of spawning. The method is tested with a two-state, one-mode avoided crossing model and a two-state, two-mode conical intersection model.

Path-integral virial estimator for reaction-rate calculation based on the quantum instanton approximation.

The quantum instanton approximation is a type of quantum transition-state theory that calculates the chemical reaction rate using the reactive flux correlation function and its low-order derivatives at time zero. Here we present several path-integral estimators for the latter quantities, which characterize the initial decay profile of the flux correlation function. As with the internal energy or heat-capacity calculation, different estimators yield different variances (and therefore different convergence properties) in a Monte Carlo calculation. Here we obtain a virial (-type) estimator by using a coordinate scaling procedure rather than integration by parts, which allows more computational benefits. We also consider two different methods for treating the flux operator, i.e., local-path and global-path approaches, in which the latter achieves a smaller variance at the cost of using second-order potential derivatives. Numerical tests are performed for a one-dimensional Eckart barrier and a model proton transfer reaction in a polar solvent, which illustrates the reduced variance of the virial estimator over the corresponding thermodynamic estimator.

Quantum reaction rate from higher derivatives of the thermal flux-flux autocorrelation function at time zero.

A quantum theory of thermal reaction rates is presented which may be viewed as an extension of the recently developed "quantum instanton" (QI) model [W. H. Miller, Y. Zhao, M. Ceotto, and S. Yang, J. Chem. Phys. 119, 1329 (2003)]. It is based on using higher derivatives of the flux-flux autocorrelation function C(t) (as given by Miller, Schwartz, and Tromp) at t=0 to construct a short time approximation for C(t). Tests of this theory on 1d and collinear reactions, both symmetric and asymmetric, show it to be more accurate than the original QI model, giving rate constants to approximately 5% for a wide range of temperature.