Expanding the CRISPR Toolbox for Engineering Lycopene Biosynthesis in Corynebacterium glutamicum.

Lycopene represents one of the central compounds in the carotenoid pathway and it exhibits a potent antioxidant ability with wide potential applications in medicine, food, and cosmetics. The microbial production of lycopene has received increasing concern in recent years. Corynebacterium glutamicum (C. glutamicum) is considered to be a safe and beneficial industrial production platform, naturally endowed with the ability to produce lycopene. However, the scarcity of efficient genetic tools and the challenge of identifying crucial metabolic genes impede further research on C. glutamicum for achieving high-yield lycopene production. To address these challenges, a novel genetic editing toolkit, CRISPR/MAD7 system, was established and developed. By optimizing the promoter, ORI and PAM sequences, the CRISPR/MAD7 system facilitated highly efficient gene deletion and exhibited a broad spectrum of PAM sites. Notably, 25 kb of DNA from the genome was successfully deleted. In addition, the CRISPR/MAD7 system was effectively utilized in the metabolic engineering of C. glutamicum, allowing for the simultaneous knockout of crtEb and crtR genes in one step to enhance the accumulation of lycopene by blocking the branching pathway. Through screening crucial genes such as crtE, crtB, crtI, idsA, idi, and cg0722, an optimal carotenogenic gene combination was obtained. Particularly, cg0722, a membrane protein gene, was found to play a vital role in lycopene production. Therefore, the CBIEbR strain was obtained by overexpressing cg0722, crtB, and crtI while strategically blocking the by-products of the lycopene pathway. As a result, the final engineered strain produced lycopene at 405.02 mg/L (9.52 mg/g dry cell weight, DCW) in fed-batch fermentation, representing the highest reported lycopene yield in C. glutamicum to date. In this study, a powerful and precise genetic tool was used to engineer C. glutamicum for lycopene production. Through the modifications between the host cell and the carotenogenic pathway, the lycopene yield was stepwise improved by 102-fold as compared to the starting strain. This study highlights the usefulness of the CRISPR/MAD7 toolbox, demonstrating its practical applications in the metabolic engineering of industrially robust C. glutamicum.

Self-adjuvanting polymeric nanovaccines enhance IFN production and cytotoxic T cell response.

Vaccines represent one of the most powerful and cost-effective innovations for controlling a wide range of infectious diseases caused by various viruses and bacteria. Unlike mRNA and DNA-based vaccines, subunit vaccines carry no risk of insertional mutagenesis and can be lyophilized for convenient transportation and long-term storage. However, existing adjuvants are often associated with toxic effect and reactogenicity, necessitating expanding the repertoire of adjuvants with better biocompatibility, for instance, designing self-adjuvating polymeric carriers. We herein report a novel subunit vaccine delivery platform constructed via in situ free radical polymerization of C7A (2-(Hexamethyleneimino) ethyl methacrylate) and acrylamide around the surface of individual protein antigens. Using ovalbumin (OVA) as a model antigen, we observed substantial increases in both diameter (∼70 nm) and surface potential (-1.18 mV) following encapsulation, referred to as n(OVA)C7A. C7A's ultra pH sensitivity with a transition pH around 6.9 allows for rapid protonation in acidic environments. This property facilitates crucial processes such as endosomal escape and major histocompatibility complex (MHC)-I-mediated antigen presentation, culminating in the substantial CD8+ T cell activation. Additionally, compared to OVA nanocapsules without the C7A components and native OVA without modifications, we observed heightened B cell activation within the germinal center, along with remarkable increases in serum antibody and cytokine production. It's important to note that mounting evidence suggests that adjuvant effects, particularly its targeted stimulation of type I interferons (IFNs), can contribute to advantageous adaptive immune responses. Beyond its exceptional potency, the nanovaccine also demonstrated robust formation of immune memory and exhibited a favorable biosafety profile. These findings collectively underscore the promising potential of our nanovaccine in the realm of immunotherapy and vaccine development.

Computational tools and algorithms for ion mobility spectrometry-mass spectrometry.

Ion mobility spectrometry-mass spectrometry (IMS-MS or IM-MS) is a powerful analytical technique that combines the gas-phase separation capabilities of IM with the identification and quantification capabilities of MS. IM-MS can differentiate molecules with indistinguishable masses but different structures (e.g., isomers, isobars, molecular classes, and contaminant ions). The importance of this analytical technique is reflected by a staged increase in the number of applications for molecular characterization across a variety of fields, from different MS-based omics (proteomics, metabolomics, lipidomics, etc.) to the structural characterization of glycans, organic matter, proteins, and macromolecular complexes. With the increasing application of IM-MS there is a pressing need for effective and accessible computational tools. This article presents an overview of the most recent free and open-source software tools specifically tailored for the analysis and interpretation of data derived from IM-MS instrumentation. This review enumerates these tools and outlines their main algorithmic approaches, while highlighting representative applications across different fields. Finally, a discussion of current limitations and expectable improvements is presented.

Accumulation of Large Ion Populations with High Ion Densities and Effects Due to Space Charge in Traveling Wave-Based Structures for Lossless Ion Manipulations (SLIM) IMS-MS.

The accumulation of very large ion populations in traveling wave (TW)-based Structures for Lossless ion Manipulations (SLIM) has been studied to better understand aspects of "in-SLIM" ion accumulation, and particularly its use in conjunction with ion mobility spectrometry (IMS). A linear SLIM ion path was implemented that had a "gate" for blocking and accumulating ions for arbitrary time periods. Removing the gate potential caused ions to exit, and the spatial distributions of accumulated ions examined. The ion populations for a set of peptides increased approximately linearly with increased accumulation times until space change effects became significant, after which the peptide precursor ion populations decreased due to growing space charge-related ion activation, reactions, and losses. Ion activation increased with added storage times and the TW amplitude. Lower amplitude TWs in the accumulation/storage region prevented or minimized ion losses or ion heating effects that can also lead to fragmentation. Our results supported the use of an accumulation region close to the SLIM entrance for speeding accumulation, minimizing ion heating, and avoiding ion population profiles that result in IMS peak tailing. Importantly, space charge-driven separations were observed for large populations of accumulated species and attributed to the opposing effects of space charge and the TW. In these separations, ion species form distributions or peaks, sometimes moving against the TW, and are ordered in the SLIM based on their mobilities. Only the highest mobility ions located closest to the gate in the trapped ion population (and where the highest ion densities were achieved) were significantly activated. The observed separations may offer utility for ion prefractionation of ions and increasing the dynamic range measurements, increasing the resolving power of IMS separations by decreasing peak widths for accumulated ion populations, and other purposes benefiting from separations of extremely large ion populations.

Deciphering ApoE Genotype-Driven Proteomic and Lipidomic Alterations in Alzheimer's Disease Across Distinct Brain Regions.

Alzheimer's disease (AD) is a neurodegenerative disease with a complex etiology influenced by confounding factors such as genetic polymorphisms, age, sex, and race. Traditionally, AD research has not prioritized these influences, resulting in dramatically skewed cohorts such as three times the number of Apolipoprotein E (APOE) ε4-allele carriers in AD relative to healthy cohorts. Thus, the resulting molecular changes in AD have previously been complicated by the influence of apolipoprotein E disparities. To explore how apolipoprotein E polymorphism influences AD progression, 62 post-mortem patients consisting of 33 AD and 29 controls (Ctrl) were studied to balance the number of ε4-allele carriers and facilitate a molecular comparison of the apolipoprotein E genotype. Lipid and protein perturbations were assessed across AD diagnosed brains compared to Ctrl brains, ε4 allele carriers (APOE4+ for those carrying 1 or 2 ε4s and APOE4- for non-ε4 carriers), and differences in ε3ε3 and ε3ε4 Ctrl brains across two brain regions (frontal cortex (FCX) and cerebellum (CBM)). The region-specific influences of apolipoprotein E on AD mechanisms showcased mitochondrial dysfunction and cell proteostasis at the core of AD pathophysiology in the post-mortem brains, indicating these two processes may be influenced by genotypic differences and brain morphology.

Magnetic nanoparticle-based immunosensors and aptasensors for mycotoxin detection in foodstuffs: An update.

Mycotoxin contamination of food crops is a global challenge due to their unpredictable occurrence and severe adverse health effects on humans. Therefore, it is of great importance to develop effective tools to prevent the accumulation of mycotoxins through the food chain. The use of magnetic nanoparticle (MNP)-assisted biosensors for detecting mycotoxin in complex foodstuffs has garnered great interest due to the significantly enhanced sensitivity and accuracy. Within such a context, this review includes the fundamentals and recent advances (2020-2023) in the area of mycotoxin monitoring in food matrices using MNP-based aptasensors and immunosensors. In this review, we start by providing a comprehensive introduction to the design of immunosensors (natural antibody or nanobody, random or site-oriented immobilization) and aptasensors (techniques for aptamer selection, characterization, and truncation). Meanwhile, special attention is paid to the multifunctionalities of MNPs (recoverable adsorbent, versatile carrier, and signal indicator) in preparing mycotoxin-specific biosensors. Further, the contribution of MNPs to the multiplexing determination of various mycotoxins is summarized. Finally, challenges and future perspectives for the practical applications of MNP-assisted biosensors are also discussed. The progress and updates of MNP-based biosensors shown in this review are expected to offer readers valuable insights about the design of MNP-based tools for the effective detection of mycotoxins in practical applications.

Significance of the antibody orientation for the lateral flow immunoassays: A mini-review.

Lateral flow immunoassays (LFIAs) are well-established and broadly commercialized tools in the field of point-of-care testing due to their simplicity, rapidity, cost-effectiveness, and low requirements for users and equipment. However, the insensitivity and the possibility of producing inaccurate results associated with conventional LFIAs have impeded their wide-ranging implementation, especially for monitoring ultra-trace level of analytes. Moreover, the heterogeneous distribution of amino acids on the surface of antibody (Ab) results in a lack of precise control over their orientation, which ultimately leads to unsatisfactory detection performance. To address those concerns, herein we provide an overview of the emerging efforts to prepare well-established LFIAs from the perspective of orientation manipulation of immobilized Abs on the nanoprobes or membranes. The preparation of excellent nanoprobes with Abs being oriented immobilized, consisting of the nanoprobe types, Ab types, and their conjugation chemistries, are reviewed. Followed by the introduction of efforts highlight the importance of directionally immobilized Ab on the membrane. The effects of Ab orientation on the analytical performance of LFIA platforms in terms of sensitivity, specificity, rapidity, reliability, cost-effectiveness, and stability are also summarized. Finally, the future development and challenges of Ab-oriented immobilization-assisted LFIAs are also discussed.

The Role of Ion Rotation in Ion Mobility: Ultrahigh-Precision Prediction of Ion Mobility Dependence on Ion Mass Distribution and Translational to Rotational Energy Transfer.

The role of ion rotation in determining ion mobilities is explored using the subtle gas phase ion mobility shifts based on differences in ion mass distributions between isotopomer ions that have been observed with ion mobility spectrometry (IMS) measurements. These mobility shifts become apparent for IMS resolving powers on the order of ∼1500 where relative mobilities (or alternatively momentum transfer collision cross sections; Ω) can be measured with a precision of ∼10 ppm. The isotopomer ions have identical structures and masses, differing only in their internal mass distributions, and their Ω differences cannot be predicted by widely used computational approaches, which ignore the dependence of Ω on the ion's rotational properties. Here, we investigate the rotational dependence of Ω, which includes changes to its collision frequency due to thermal rotation as well as the coupling of translational to rotational energy transfer. We show that differences in rotational energy transfer during ion-molecule collisions provide the major contribution to isotopomer ion separations, with only a minor contribution due to an increase in collision frequency due to ion rotation. Modeling including these factors allowed for differences in Ω to be calculated that precisely mirror the experimental separations. These findings also highlight the promise of pairing high-resolution IMS measurements with theory and computation for improved elucidation of subtle structural differences between ions.

mzapy: An Open-Source Python Library Enabling Efficient Extraction and Processing of Ion Mobility Spectrometry-Mass Spectrometry Data in the MZA File Format.

Analysis of ion mobility spectrometry (IMS) data has been challenging and limited the full utility of these measurements. Unlike liquid chromatography-mass spectrometry, where a plethora of tools with well-established algorithms exist, the incorporation of the additional IMS dimension requires upgrading existing computational pipelines and developing new algorithms to fully exploit the advantages of the technology. We have recently reported MZA, a new and simple mass spectrometry data structure based on the broadly supported HDF5 format and created to facilitate software development. While this format is inherently supportive of application development, the availability of core libraries in popular programming languages with standard mass spectrometry utilities will facilitate fast software development and broader adoption of the format. To this end, we present a Python package, mzapy, for efficient extraction and processing of mass spectrometry data in the MZA format, especially for complex data containing ion mobility spectrometry dimension. In addition to raw data extraction, mzapy contains supporting utilities enabling tasks including calibration, signal processing, peak finding, and generating plots. Being implemented in pure Python and having minimal and largely standardized dependencies makes mzapy uniquely suited to application development in the multiomics domain. The mzapy package is free and open-source, includes comprehensive documentation, and is structured to support future extension to meet the evolving needs of the MS community. The software source code is freely available at https://github.com/PNNL-m-q/mzapy.

Heterogeneity changes of active bacterial community on cigar filler leaves after fermentation based on metagenome.

Microorganisms play an important role in cigar fermentation. To further explore the dynamic changes of bacterial community composition, the changes of surface bacterial diversity of cigar filler leaves were investigated in the present study by high-throughput sequencing technology. It was found that the surface bacterial richness was declined after fermentation, and the dominant microorganisms on the surface of cigar filler leaves evolved from Pseudomonas spp. and Sphingomonas spp. before fermentation to Staphylococcus spp. after fermentation. The chemical composition and sensory quality evaluation of cigar filler leaves were closely related to the changes of surface bacterial community. The changes of the dominant surface bacterial community led to the differences of metabolic functions, among which the metabolic pathways such as the synthesis of secondary metabolites, carbon metabolism, and amino acid biosynthesis were significantly different. The results provide a basis for clarifying the roles of bacteria in fermentation of cigar filler leaves.

LipidOz enables automated elucidation of lipid carbon-carbon double bond positions from ozone-induced dissociation mass spectrometry data.

Lipids play essential roles in many biological processes and disease pathology, but unambiguous identification of lipids is complicated by the presence of multiple isomeric species differing by fatty acyl chain length, stereospecifically numbered (sn) position, and position/stereochemistry of double bonds. Conventional liquid chromatography-mass spectrometry (LC-MS/MS) analyses enable the determination of fatty acyl chain lengths (and in some cases sn position) and number of double bonds, but not carbon-carbon double bond positions. Ozone-induced dissociation (OzID) is a gas-phase oxidation reaction that produces characteristic fragments from lipids containing double bonds. OzID can be incorporated into ion mobility spectrometry (IMS)-MS instruments for the structural characterization of lipids, including additional isomer separation and confident assignment of double bond positions. The complexity and repetitive nature of OzID data analysis and lack of software tool support have limited the application of OzID for routine lipidomics studies. Here, we present an open-source Python tool, LipidOz, for the automated determination of lipid double bond positions from OzID-IMS-MS data, which employs a combination of traditional automation and deep learning approaches. Our results demonstrate the ability of LipidOz to robustly assign double bond positions for lipid standard mixtures and complex lipid extracts, enabling practical application of OzID for future lipidomics.

Evaluating Software Tools for Lipid Identification from Ion Mobility Spectrometry-Mass Spectrometry Lipidomics Data.

The unambiguous identification of lipids is a critical component of lipidomics studies and greatly impacts the interpretation and significance of analyses as well as the ultimate biological understandings derived from measurements. The level of structural detail that is available for lipid identifications is largely determined by the analytical platform being used. Mass spectrometry (MS) coupled with liquid chromatography (LC) is the predominant combination of analytical techniques used for lipidomics studies, and these methods can provide fairly detailed lipid identification. More recently, ion mobility spectrometry (IMS) has begun to see greater adoption in lipidomics studies thanks to the additional dimension of separation that it provides and the added structural information that can support lipid identification. At present, relatively few software tools are available for IMS-MS lipidomics data analysis, which reflects the still limited adoption of IMS as well as the limited software support. This fact is even more pronounced for isomer identifications, such as the determination of double bond positions or integration with MS-based imaging. In this review, we survey the landscape of software tools that are available for the analysis of IMS-MS-based lipidomics data and we evaluate lipid identifications produced by these tools using open-access data sourced from the peer-reviewed lipidomics literature.

Multistage-Responsive Dual-Enzyme Nanocascades for Synergistic Radiosensitization-Starvation Cancer Therapy.

Radiotherapy is a common cancer treatment approach in clinical practice, yet its efficacy has been restricted by tumor hypoxia. Nanomaterials-mediated systemic delivery of glucose oxidase (GOx) and catalase (CAT) or CAT-like nanoenzymes holds the potential to enhance tumor oxygenation. However, they face the challenge of intermediate (hydrogen peroxide [H2 O2 ]) escape during systemic circulation if the enzyme pair is not closely placed to largely decompose H2 O2 , leading to oxidative stress on normal tissues. In the present study, a oxygen-generating nanocascade, n(GOx-CAT)C7A , constructed by strategically placing an enzymatic cascade (GOx and CAT) within a polymeric coating rich in hexamethyleneimine (C7A) moieties, is reported. During blood circulation, C7A remains predominantly non-protonated , achieving prolonged blood circulation due to its low-fouling surface. Once n(GOx-CAT)C7A reaches the tumor site, the acidic tumor microenvironment (TME) induces protonation of C7A moieties, resulting in a positively charged surface for enhanced tumor transcytosis. Moreover, GOx and CAT are covalently conjugated into close spatial proximity (<10 nm) for effective H2 O2  elimination. As demonstrated by the in vivo results, n(GOx-CAT)C7A achieves effective tumor retention and oxygenation, potent radiosensitization and antitumor effects. Such a dual-enzyme nanocascade for smart O2  delivery holds great potential for enhancing the hypoxia-compromised cancer therapies.

MZA: A Data Conversion Tool to Facilitate Software Development and Artificial Intelligence Research in Multidimensional Mass Spectrometry.

Modern mass spectrometry-based workflows employing hybrid instrumentation and orthogonal separations collect multidimensional data, potentially allowing deeper understanding in omics studies through adoption of artificial intelligence methods. However, the large volume of these rich spectra challenges existing data storage and access technologies, therefore precluding informatics advancements. We present MZA (pronounced m-za), the mass-to-charge (m/z) generic data storage and access tool designed to facilitate software development and artificial intelligence research in multidimensional mass spectrometry measurements. Composed of a data conversion tool and a simple file structure based on the HDF5 format, MZA provides easy, cross-platform and cross-programming language access to raw MS-data, enabling fast development of new tools in data science programming languages such as Python and R. The software executable, example MS-data and example Python and R scripts are freely available at https://github.com/PNNL-m-q/mza.

Adaptive laboratory evolution to obtain furfural tolerant Saccharomyces cerevisiae for bioethanol production and the underlying mechanism.

Introduction: Furfural, a main inhibitor produced during pretreatment of lignocellulose, has shown inhibitory effects on S. cerevisiae. Method: In the present study, new strains named 12-1 with enhanced resistance to furfural were obtained through adaptive laboratory evolution, which exhibited a shortened lag phase by 36 h, and an increased ethanol conversion rate by 6.67% under 4 g/L furfural. Results and Discussion: To further explore the mechanism of enhanced furfural tolerance, ADR1_1802 mutant was constructed by CRISPR/Cas9 technology, based on whole genome re-sequencing data. The results indicated that the time when ADR1_1802 begin to grow was shortened by 20 h compared with reference strain (S. cerevisiae CEN.PK113-5D) when furfural was 4 g/L. Additionally, the transcription levels of GRE2 and ADH6 in ADR1_ 1802 mutant were increased by 53.69 and 44.95%, respectively, according to real-time fluorescence quantitative PCR analysis. These findings suggest that the enhanced furfural tolerance of mutant is due to accelerated furfural degradation. Importance: Renewable carbon worldwide is vital to achieve "zero carbon" target. Bioethanol obtained from biomass is one of them. To make bioethanol price competitive to fossil fuel, higher ethanol yield is necessary, therefore, monosaccharide produced during biomass pretreatment should be effectively converted to ethanol by Saccharomyces cerevisiae. However, inhibitors formed by glucose or xylose oxidation could make ethanol yield lower. Thus, inhibitor tolerant Saccharomyces cerevisiae is important to this process. As one of the main component of pretreatment hydrolysate, furfural shows obvious impact on growth and ethanol production of Saccharomyces cerevisiae. To get furfural tolerant Saccharomyces cerevisiae and find the underlying mechanism, adaptive laboratory evolution and CRISPR/Cas9 technology were applied in the present study.

Enhanced Expression of Alcohol Dehydrogenase I in Pichia pastoris Reduces the Content of Acetaldehyde in Wines.

Acetaldehyde is an important carbonyl compound commonly detected in wines. A high concentration of acetaldehyde can affect the flavor of wines and result in adverse effects on human health. Alcohol dehydrogenase I (ADH1) in Saccharomyces cerevisiae catalyzes the reduction reaction of acetaldehyde into ethanol in the presence of cofactors, showing the potential to reduce the content of acetaldehyde in wines. In this study, ADH1 was successfully expressed in Pichia pastoris GS115 based on codon optimization. Then, the expression level of ADH1 was enhanced by replacing its promoter with optimized promoters and increasing the copy number of the expression cassette, with ADH1 being purified using nickel column affinity chromatography. The enzymatic activity of purified ADH1 reached 605.44 ± 44.30 U/mg. The results of the effect of ADH1 on the content of acetaldehyde in wine revealed that the acetaldehyde content of wine samples was reduced from 168.05 ± 0.55 to 113.17 ± 6.08 mg/L with the addition of 5 mM NADH and the catalysis of ADH1, and from 135.53 ± 4.08 to 52.89 ± 2.20 mg/L through cofactor regeneration. Our study provides a novel approach to reducing the content of acetaldehyde in wines through enzymatic catalysis.

AgNPs/nGOx/Apra nanocomposites for synergistic antimicrobial therapy and scarless skin recovery.

The misuse of antimicrobials has caused a remarkable increase of antibiotic-resistant bacteria. Developing novel antimicrobial agents with high activity and low rates of resistance development is in great demand yet challenging. In this context, we developed a novel cascaded AgNPs/nGOx/Apra nanocomposite for combinational antimicrobial therapy. Glucose oxidase nanocapsules (nGOx) in the nanocomposites can convert tissue glucose into H2O2, which in turn accelerates the erosion of AgNPs into Ag+, giving rise to a synergistic antibiotic/starving-like/metal ion therapeutic effect. An in vitro antimicrobial study of the nanocomposites demonstrated rapid bacterial killing, significant bacterial growth inhibition and broad antimicrobial spectra at a low antibiotic dose. More importantly, topical and microneedle-assisted deliveries of the nanocomposites resulted in rapid scarless skin recovery in both rabbit and mouse models. This nanocomposite platform opens up a new avenue for research and clinical applications to battle against microbial infections and reduce antibiotic-resistant rates.

A Histoplasma capsulatum Lipid Metabolic Map Identifies Antifungal Targets.

Lipids play a fundamental role in fungal cell biology, being essential cell membrane components and major targets of antifungal drugs. A deeper knowledge of lipid metabolism is key for developing new drugs and a better understanding of fungal pathogenesis. Here, we built a comprehensive map of the Histoplasma capsulatum lipid metabolic pathway by incorporating proteomic and lipidomic analyses. We performed genetic complementation and overexpression of H. capsulatum genes in Saccharomyces cerevisiae to validate reactions identified in the map and to determine enzymes responsible for catalyzing orphan reactions. The map led to the identification of both the fatty acid desaturation and the sphingolipid biosynthesis pathways as targets for drug development. We found that the sphingolipid biosynthesis inhibitor myriocin, the fatty acid desaturase inhibitor thiocarlide, and the fatty acid analog 10-thiastearic acid inhibit H. capsulatum growth in nanomolar to low-micromolar concentrations. These compounds also reduced the intracellular infection in an alveolar macrophage cell line. Overall, this lipid metabolic map revealed pathways that can be targeted for drug development. IMPORTANCE It is estimated that 150 people die per hour due to the insufficient therapeutic treatments to combat fungal infections. A major hurdle to developing antifungal therapies is the scarce knowledge on the fungal metabolic pathways and mechanisms of virulence. In this context, fungal lipid metabolism is an excellent candidate for developing drugs due to its essential roles in cellular scaffolds, energy storage, and signaling transductors. Here, we provide a detailed map of Histoplasma capsulatum lipid metabolism. The map revealed points of this fungus lipid metabolism that can be targeted for developing antifungal drugs.

A Novel and Efficient Genome Editing Tool Assisted by CRISPR-Cas12a/Cpf1 for Pichia pastoris.

Pichia pastoris has been widely exploited for the heterologous expression of proteins in both industry and academia. Recently, it has been shown to be a potentially good chassis host for the production of high-value chemicals and pharmaceuticals. Effective synthetic biology tools for genetic engineering are essential for industrial and biotechnological research in this yeast. Here, we describe a novel and efficient genome editing method mediated by the CRISPR-Cpf1 system, which could facilitate the deletion of large DNA fragments and integration of multiplexed gene fragments. The CRISPR-Cpf1 system exhibited a precise and high editing efficiency for single-gene disruption (99 ± 0.8%), duplex genome editing (65 ± 2.5% to 80 ± 3%), and triplex genome editing (30 ± 2.5%). In addition, the deletion of large DNA fragments of 20kb and one-step integration of multiple genes were first achieved using the developed CRISPR-Cpf1 system. Taken together, this study provides an efficient and simple gene editing tool for P. pastoris. The novel multiloci gene integration method mediated by CRISPR-Cpf1 may accelerate the ability to engineer this methylotrophic yeast for metabolic engineering and genome evolution in both biotechnological and biomedical applications.

AutoCCS: automated collision cross-section calculation software for ion mobility spectrometry-mass spectrometry.

MOTIVATION: Ion mobility spectrometry (IMS) separations are increasingly used in conjunction with mass spectrometry (MS) for separation and characterization of ionized molecular species. Information obtained from IMS measurements includes the ion's collision cross section (CCS), which reflects its size and structure and constitutes a descriptor for distinguishing similar species in mixtures that cannot be separated using conventional approaches. Incorporating CCS into MS-based workflows can improve the specificity and confidence of molecular identification. At present, there is no automated, open-source pipeline for determining CCS of analyte ions in both targeted and untargeted fashion, and intensive user-assisted processing with vendor software and manual evaluation is often required. RESULTS: We present AutoCCS, an open-source software to rapidly determine CCS values from IMS-MS measurements. We conducted various IMS experiments in different formats to demonstrate the flexibility of AutoCCS for automated CCS calculation: (i) stepped-field methods for drift tube-based IMS (DTIMS), (ii) single-field methods for DTIMS (supporting two calibration methods: a standard and a new enhanced method) and (iii) linear calibration for Bruker timsTOF and non-linear calibration methods for traveling wave based-IMS in Waters Synapt and Structures for Lossless Ion Manipulations. We demonstrated that AutoCCS offers an accurate and reproducible determination of CCS for both standard and unknown analyte ions in various IMS-MS platforms, IMS-field methods, ionization modes and collision gases, without requiring manual processing. AVAILABILITY AND IMPLEMENTATION: https://github.com/PNNL-Comp-Mass-Spec/AutoCCS. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Demo datasets are publicly available at MassIVE (Dataset ID: MSV000085979).