Error correction of microchip synthesized genes using Surveyor nuclease

The development of economical and high-throughput gene synthesis technology has been hampered by the high occurrence of errors in the synthesized products, which requires expensive labor and time to correct. Here, we describe an error correction reaction (ECR), which employs Surveyor, a mismatch-specific DNA endonuclease, to remove errors from synthetic genes. In ECR reactions, errors are revealed as mismatches by re-annealing of the synthetic gene products. Mismatches are recognized and excised by a combination of mismatch-specific endonuclease and 3′→5′ exonuclease activities in the reaction mixture. Finally, overlap extension polymerase chain reaction (OE-PCR) re-assembles the resulting fragments into intact genes. The process can be iterated for increased fidelity. With two iterations, we were able to reduce errors in synthetic genes by >16-fold, yielding a final error rate of ∼1 in 8700 bp

Spatial Pathomics Toolkit for Quantitative Analysis of Podocyte Nuclei with Histology and Spatial Transcriptomics Data in Renal Pathology

Podocytes, specialized epithelial cells that envelop the glomerular capillaries, play a pivotal role in maintaining renal health. The current description and quantification of features on pathology slides are limited, prompting the need for innovative solutions to comprehensively assess diverse phenotypic attributes within Whole Slide Images (WSIs). In particular, understanding the morphological characteristics of podocytes, terminally differentiated glomerular epithelial cells, is crucial for studying glomerular injury. This paper introduces the Spatial Pathomics Toolkit (SPT) and applies it to podocyte pathomics. The SPT consists of three main components: (1) instance object segmentation, enabling precise identification of podocyte nuclei; (2) pathomics feature generation, extracting a comprehensive array of quantitative features from the identified nuclei; and (3) robust statistical analyses, facilitating a comprehensive exploration of spatial relationships between morphological and spatial transcriptomics features.The SPT successfully extracted and analyzed morphological and textural features from podocyte nuclei, revealing a multitude of podocyte morphomic features through statistical analysis. Additionally, we demonstrated the SPT's ability to unravel spatial information inherent to podocyte distribution, shedding light on spatial patterns associated with glomerular injury. By disseminating the SPT, our goal is to provide the research community with a powerful and user-friendly resource that advances cellular spatial pathomics in renal pathology. The implementation and its complete source code of the toolkit are made openly accessible at https://github.com/hrlblab/spatial_pathomics

Circular Polymerase Extension Cloning of Complex Gene Libraries and Pathways

High-throughput genomics and the emerging field of synthetic biology demand ever more convenient, economical, and efficient technologies to assemble and clone genes, gene libraries and synthetic pathways. Here, we describe the development of a novel and extremely simple cloning method, circular polymerase extension cloning (CPEC). This method uses a single polymerase to assemble and clone multiple inserts with any vector in a one-step reaction in vitro. No restriction digestion, ligation, or single-stranded homologous recombination is required. In this study, we elucidate the CPEC reaction mechanism and demonstrate its usage in demanding synthetic biology applications such as one-step assembly and cloning of complex combinatorial libraries and multi-component pathways

Persistent sulfate formation from London Fog to Chinese haze

Sulfate aerosols exert profound impacts on human and ecosystem health, weather, and climate, but their formation mechanism remains uncertain. Atmospheric models consistently underpredict sulfate levels under diverse environmental conditions. From atmospheric measurements in two Chinese megacities and complementary laboratory experiments, we show that the aqueous oxidation of SO2 by NO2 is key to efficient sulfate formation but is only feasible under two atmospheric conditions: on fine aerosols with high relative humidity and NH3 neutralization or under cloud conditions. Under polluted environments, this SO2 oxidation process leads to large sulfate production rates and promotes formation of nitrate and organic matter on aqueous particles, exacerbating severe haze development. Effective haze mitigation is achievable by intervening in the sulfate formation process with enforced NH3 and NO2 control measures. In addition to explaining the polluted episodes currently occurring in China and during the 1952 London Fog, this sulfate production mechanism is widespread, and our results suggest a way to tackle this growing problem in China and much of the developing world

Genetic Assembly, Error-Correction and a High-Throughput Screening Strategy for Protein Expression Optimization

<p>Various types of genetic constructs are widely used as diagnostic, prophylactic, and therapeutic tools for human diseases. They are also the workhorse in biotech and pharmaceutical industry for production of therapeutic antibodies and proteins. Since the majority of the genetic constructs encode protein products, it is therefore of tremendous value to human health and the society that we could find a way to fine-tune and optimize genetic constructs and hence protein expression for achieving maximal potency or long-lasting effects in therapeutics or for obtaining highest yields in pharmaceutical protein production. However, for protein-coding genes to be expressed in a heterologous host, the coding sequences need to be optimized by using synonymous codons to achieve reasonable levels of expression, if at all. Since codon optimization is done in a protein-by-protein basis with respect to specific host organisms, tissue/cell types, even health conditions, and there is no set of standard rules to follow, this process is still very unpredictable and time-consuming.</p><p>This thesis presents the development of a feasible platform for solving the problem of optimizing regular and long DNA constructs for academic or industrial purposes through the development of a novel cloning method for complex gene libraries, and based on the library expression system constructed in such manner, a platform for high-throughput screening of codon-optimized and error-corrected proteins, and a novel protocol for screening long gene constructs which could be extremely difficult to achieve by using regular screening methods. This multi-step platform has the potential for studying the natural systems: how codon bias correlates to protein expression efficiency, for generating improved pharmaceutical proteins and enhanced DNA vaccines and for constructing improved genome libraries.</p>Dissertatio

Prevalence of colistin-resistant mcr-1-positive Escherichia coli isolated from children patients with diarrhoea in Shanghai, 2016–2021

ABSTRACT: Objectives: The emergence of the plasmid-mediated colistin resistance 1 (mcr-1) of Escherichia coli has become a global health concern. This study reports the prevalence of mcr-1 among E. coli isolates from patients with diarrheal disease in Shanghai and the genetic characterization of mcr-1-harbouring plasmids. Methods: A total of 1723 E. coli strains were collected from the faeces of patients with diarrheal disease in all sentinel hospitals in Shanghai from 2016 to 2021. Antimicrobial susceptibility testing was performed by broth microdilution and plasmid conjunction transfer assay was carried out using E. coli C600 as the recipient. The mcr-1-positive E. coli strains (MCRPEC) were subjected to molecular characterization and bioinformatic analysis of the mcr-1-bearing plasmids that they harboured. Results: Only 5 (0.28%) strains were found to harbour the mcr-1 gene using PCR screening. Plasmid conjugation assay and whole-genome sequencing indicated that EC16500, one MCRPEC strain that co-exhibited mcr-1, blaTEM-1, blaOXA-1, qnrS1, qnrS2, arr-3, and catB3, could be conjugated to EC C600 by horizontal transfer with an average efficiency of 3.2 × 10−5. The plasmid pEC16500 harboured similar backbones as p70_2_15, pECGD-8–33, pNCYU-29–19–1_MCR1, and pIBMC_mcr1, and was shown to be encoded within a type IV secretion system (T4SS)-containing 32.6 kbp IncX4, next to the pap2-like membrane-associated gene, to form a 2.4-kb cassette. Furthermore, sequencing and phylogenetic analyses revealed a similarity between other MCR-1-homolog proteins, indicating that the five E. coli isolates were colistin-resistant. Conclusion: Our data represents a significant snapshot of colistin resistance mcr-1 genes and highlights the need to increase active surveillance, especially among children under five years of age, in Shanghai. Great effort needs to be taken to avoid further dissemination of plasmid-mediated colistin resistance among clinically relevant Gram-negative bacterial pathogens

A Lightweight Object Detection Framework for Remote Sensing Images

Onboard real-time object detection in remote sensing images is a crucial but challenging task in this computation-constrained scenario. This task not only requires the algorithm to yield excellent performance but also requests limited time and space complexity of the algorithm. However, previous convolutional neural networks (CNN) based object detectors for remote sensing images suffer from heavy computational cost, which hinders them from being deployed on satellites. Moreover, an onboard detector is desired to detect objects at vastly different scales. To address these issues, we proposed a lightweight one-stage multi-scale feature fusion detector called MSF-SNET for onboard real-time object detection of remote sensing images. Using lightweight SNET as the backbone network reduces the number of parameters and computational complexity. To strengthen the detection performance of small objects, three low-level features are extracted from the three stages of SNET respectively. In the detection part, another three convolutional layers are designed to further extract deep features with rich semantic information for large-scale object detection. To improve detection accuracy, the deep features and low-level features are fused to enhance the feature representation. Extensive experiments and comprehensive evaluations on the openly available NWPU VHR-10 dataset and DIOR dataset are conducted to evaluate the proposed method. Compared with other state-of-art detectors, the proposed detection framework has fewer parameters and calculations, while maintaining consistent accuracy

Table_4_Prediction value of the genetic risk of type 2 diabetes on the amnestic mild cognitive impairment conversion to Alzheimer’s disease.XLSX

Amnestic mild cognitive impairment (aMCI) and Type 2 diabetes mellitus (T2DM) are both important risk factors for Alzheimer’s disease (AD). We aimed to investigate whether a T2DM-specific polygenic risk score (PRSsT2DM) can predict the conversion of aMCI to AD and further explore the underlying neurological mechanism. All aMCI patients were from the Alzheimer’s disease Neuroimaging Initiative (ADNI) database and were divided into conversion (aMCI-C, n = 164) and stable (aMCI-S, n = 222) groups. PRSsT2DM was calculated by PRSice-2 software to explore the predictive efficacy of the aMCI conversion to AD. We found that PRSsT2DM could independently predict the aMCI conversion to AD after removing the common variants of these two diseases. PRSsT2DM was significantly negatively correlated with gray matter volume (GMV) of the right superior frontal gyrus in the aMCI-C group. In all aMCI patients, PRSsT2DM was significantly negatively correlated with the cortical volume of the right superior occipital gyrus. The cortical volume of the right superior occipital gyrus could significantly mediate the association between PRSsT2DM and aMCI conversion. Gene-based analysis showed that T2DM-specific genes are highly expressed in cortical neurons and involved in ion and protein binding, neural development and generation, cell junction and projection, and PI3K-Akt and MAPK signaling pathway, which might increase the aMCI conversion by affecting the Tau phosphorylation and amyloid-beta (Aβ) accumulation. Therefore, the PRSsT2DM could be used as a measure to predict the conversion of aMCI to AD.</p

Table_1_Prediction value of the genetic risk of type 2 diabetes on the amnestic mild cognitive impairment conversion to Alzheimer’s disease.docx

Amnestic mild cognitive impairment (aMCI) and Type 2 diabetes mellitus (T2DM) are both important risk factors for Alzheimer’s disease (AD). We aimed to investigate whether a T2DM-specific polygenic risk score (PRSsT2DM) can predict the conversion of aMCI to AD and further explore the underlying neurological mechanism. All aMCI patients were from the Alzheimer’s disease Neuroimaging Initiative (ADNI) database and were divided into conversion (aMCI-C, n = 164) and stable (aMCI-S, n = 222) groups. PRSsT2DM was calculated by PRSice-2 software to explore the predictive efficacy of the aMCI conversion to AD. We found that PRSsT2DM could independently predict the aMCI conversion to AD after removing the common variants of these two diseases. PRSsT2DM was significantly negatively correlated with gray matter volume (GMV) of the right superior frontal gyrus in the aMCI-C group. In all aMCI patients, PRSsT2DM was significantly negatively correlated with the cortical volume of the right superior occipital gyrus. The cortical volume of the right superior occipital gyrus could significantly mediate the association between PRSsT2DM and aMCI conversion. Gene-based analysis showed that T2DM-specific genes are highly expressed in cortical neurons and involved in ion and protein binding, neural development and generation, cell junction and projection, and PI3K-Akt and MAPK signaling pathway, which might increase the aMCI conversion by affecting the Tau phosphorylation and amyloid-beta (Aβ) accumulation. Therefore, the PRSsT2DM could be used as a measure to predict the conversion of aMCI to AD.</p