Comparison of Current Methods for Signal Peptide Prediction in Phytoplasmas

Exploring the secretome of Corynebacterium glutamicum ATCC 13032

The demand for alternative sources of food proteins is increasing due to the limitations and challenges associated with conventional food production. Advances in biotechnology have enabled the production of proteins using microorganisms, thus prompting the exploration of attractive microbial hosts capable of producing functional proteins in high titers. Corynebacterium glutamicum is widely used in industry for the production of amino acids and has many advantages as a host organism for recombinant protein production. However, its performance in this area is limited by low yields of target proteins and high levels of native protein secretion. Despite representing a challenge for heterologous protein production, the C. glutamicum secretome has not been fully characterized. In this study, state-of-the-art mass spectrometry-based proteomics was used to identify and analyze the proteins secreted by C. glutamicum. Both the wild-type strain and a strain that produced and secreted a recombinant β-lactoglobulin protein were analyzed. A total of 427 proteins were identified in the culture supernatants, with 148 predicted to possess a secretion signal peptide. MS-based proteomics on the secretome enabled a comprehensive characterization and quantification (based on abundance) of the secreted proteins through label-free quantification (LFQ). The top 12 most abundant proteins accounted for almost 80% of the secretome. These are uncharacterized proteins of unknown function, resuscitation promoting factors, protein PS1, Porin B, ABC-type transporter protein and hypothetical membrane protein. The data can be leveraged for protein production by, e.g., utilizing the signal peptides of the most abundant proteins to improve secretion of heterologous proteins. In addition, secretory stress can potentially be alleviated by inactivating non-essential secreted proteins. Here we provide targets by identifying the most abundant, secreted proteins of which majority are of unknown function. The data from this study can thus provide valuable insight for researchers looking to improve protein secretion and optimize C. glutamicum as a host for secretory protein production.

Phytoplasma: A plant pathogen that cannot be ignored in agricultural production-Research progress and outlook

Phytoplasmas are phloem-restricted plant-pathogenic bacteria transmitted by insects. They cause diseases in a wide range of host plants, resulting in significant economic and ecological losses worldwide. Research on phytoplasmas has a long history, with significant progress being made in the past 30 years. Notably, with the rapid development of phytoplasma research, scientists have identified the primary agents involved in phytoplasma transmission, established classification and detection systems for phytoplasmas, and 243 genomes have been sequenced and assembled completely or to draft quality. Multiple possible phytoplasma effectors have been investigated, elucidating the molecular mechanisms by which phytoplasmas manipulate their hosts. This review summarizes recent advances in phytoplasma research, including identification techniques, host range studies, whole- or draft-genome sequencing, effector pathogenesis and disease control methods. Additionally, future research directions in the field of phytoplasma research are discussed.

DeTox: a pipeline for the detection of toxins in venomous organisms

Venomous organisms have independently evolved the ability to produce toxins 101 times during their evolutionary history, resulting in over 200 000 venomous species. Collectively, these species produce millions of toxins, making them a valuable resource for bioprospecting and understanding the evolutionary mechanisms underlying genetic diversification. RNA-seq is the preferred method for characterizing toxin repertoires, but the analysis of the resulting data remains challenging. While early approaches relied on similarity-based mapping to known toxin databases, recent studies have highlighted the importance of structural features for toxin detection. The few existing pipelines lack an integration between these complementary approaches, and tend to be difficult to run for non-experienced users. To address these issues, we developed DeTox, a comprehensive and user-friendly tool for toxin research. It combines fast execution, parallelization and customization of parameters. DeTox was tested on published transcriptomes from gastropod mollusks, cnidarians and snakes, retrieving most putative toxins from the original articles and identifying additional peptides as potential toxins to be confirmed through manual annotation and eventually proteomic analysis. By integrating a structure-based search with similarity-based approaches, DeTox allows the comprehensive characterization of toxin repertoire in poorly-known taxa. The effect of the taxonomic bias in existing databases is minimized in DeTox, as mirrored in the detection of unique and divergent toxins that would have been overlooked by similarity-based methods. DeTox streamlines toxin annotation, providing a valuable tool for efficient identification of venom components that will enhance venom research in neglected taxa.

Antimicrobial peptides in Dendrobium officinale: Genomic parameters, peptide structures, and gene expression patterns

A weak codon usage bias was found in Dendrobium catenatum (D. officiale) antimicrobial peptides (AMPs), after the analysis of relative synonymous codon usage, GC contents, and the effective number of codons. The codon usage preference was mainly influenced by natural selection pressure. The self-optimized prediction method and SWISS-MODEL were applied for peptide structural and domain analyses, and some typical antimicrobial domains were found in D. officinale AMP amino sequences, such as knot1 domain, gibberellins-stimulated domain, cupin_1 domain, defensin_like domain, and SLR1-BP (S locus-related glycoprotein 1 binding pollen coat protein) domain. To investigate the AMPs gene expression pattern, abiotic stresses, such as salt stress, drought stress, salicylic acid (SA), and methyl jasmonate (JA), were applied and the gene expression levels were detected by the real-time fluorescent quantitative polymerase chain reaction. Results showed that, even though the basic AMPs gene expressions were low, some AMPs can still be induced by salt dress, while the drought dress did not show the same impact. The SA and JA signaling pathways might be involved in most of the AMPs expressions. The natural selection of the D. officinale AMPs and thus forming diverse types of AMPs enhanced the plant's innate immunity and disease resistance capability, which would lead to a better understanding of the molecular mechanism for D. officinale adapting to the environment. The finding that salt stress, SA, and JA signaling pathways can induce AMP expression lays a foundation for the further development and functional verification of D. officinale AMPs.

Genome-wide identification, expression analysis, and transcriptome analysis of the IAA gene family in Zoysia japonica

BACKGROUND

AUX/IAA is an essential signaling molecule and has great physiological importance in various plants, but its function in Zoysia japonica remains unknown.

METHODS AND RESULTS

Genome-wide identification and analysis of AUX/IAA genes used bioinformatics methods to investigate the ZjIAA genes' expression of exogenous IAA hydroponics treatment for 2 h by qRT-PCR, control and exogenous IAA treated zoysia were subjected to transcriptome sequencing. ZjIAAs were distributed across the 13 subfamilies by phylogenetic analysis with Oryza sativa and Arabidopsis thaliana. Multiple sequence alignment revealed that the majority of genes were non-canonical ZjIAAs with incomplete domain. The optimal growth concentration of the IAA hormone was 0.05 mM, and the qRT-PCR analysis revealed that eight ZjIAAs were differentially expressed, with seven genes considerably upregulating and one gene significantly downregulating. The result of transcriptome sequencing revealed that 515 differentially expressed genes (DEGs) were identified, with 344 upregulated genes and 171 downregulated genes. A total of 18 genes were annotated as involved in the plant hormone signal transduction pathway. And 8 ZjIAAs exhibited distinct expressions, 7 upregulated, and only one downregulated, according to the qRT-PCR study.

CONCLUSIONS

Genome-wide identification and analysis increased the understanding of the evolution and function of the IAA family in zoysia. DEGs of control and treatment with 0.05 mM exogenous IAA hormone were investigated by transcriptome sequencing. ZjIAAs had substantial variations in the expression of associated genes, with the majority of genes upregulated and 18 genes implicated in plant hormone signal transduction.

A Novel R2R3-MYB Transcription Factor SbMYB12 Positively Regulates Baicalin Biosynthesis in Scutellaria baicalensis Georgi

Scutellaria baicalensis Georgi is an annual herb from the Scutellaria genus that has been extensively used as a traditional medicine for over 2000 years in China. Baicalin and other flavonoids have been identified as the principal bioactive ingredients. The biosynthetic pathway of baicalin in S. baicalensis has been elucidated; however, the specific functions of R2R3-MYB TF, which regulates baicalin synthesis, has not been well characterized in S. baicalensis to date. Here, a S20 R2R3-MYB TF (SbMYB12), which encodes 263 amino acids with a length of 792 bp, was expressed in all tested tissues (mainly in leaves) and responded to exogenous hormone methyl jasmonate (MeJA) treatment. The overexpression of SbMYB12 significantly promoted the accumulation of flavonoids such as baicalin and wogonoside in S. baicalensis hairy roots. Furthermore, biochemical experiments revealed that SbMYB12 is a nuclear-localized transcription activator that binds to the SbCCL7-4, SbCHI-2, and SbF6H-1 promoters to activate their expression. These results illustrate that SbMYB12 positively regulates the generation of baicalin and wogonoside. In summary, this work revealed a novel S20 R2R3-MYB regulator and enhances our understanding of the transcriptional and regulatory mechanisms of baicalin biosynthesis, as well as sheds new light on metabolic engineering in S. baicalensis.

Putative Protein Discovery from Microalgal Genomes as a Synthetic Biology Protein Library for Heavy Metal Bio-Removal

Simple Summary

Nowadays, heavy metal polluted wastewater is one of the global challenges that leads to an insufficient supply of clean water. Taking advantage of what nature has to offer, several organisms, including microalgae, can natively bioremediate these heavy metals. However, the effectiveness of such processes does not meet expectations, especially with the increasing amount of pollution in today’s world. Therefore, with the goal of creating effective strains, synthetic biology via bioengineering is widely used as a strategy to enhance the heavy metal bio-removing capability, either by directly engineering the native ability of organisms or by transferring the ability to a more suitable host. In order to do so, a list of genes or proteins involved in the processes is crucial for stepwise engineering. Yet, a large amount of information remains to be discovered. In this work, a comprehensive library of putative proteins that are involved in heavy metal bio-removal from microalgae was constructed. Moreover, with the development of machine learning, the 3D structures of these proteins are also predicted, using machine learning-based methods, to aid the use of synthetic biology further.

Abstract

Synthetic biology is a principle that aims to create new biological systems with particular functions or to redesign the existing ones through bioengineering. Therefore, this principle is often utilized as a tool to put the knowledge learned to practical use in actual fields. However, there is still a great deal of information remaining to be found, and this limits the possible utilization of synthetic biology, particularly on the topic that is the focus of the present work—heavy metal bio-removal. In this work, we aim to construct a comprehensive library of putative proteins that might support heavy metal bio-removal. Hypothetical proteins were discovered from Chlorella and Scenedesmus genomes and extensively annotated. The protein structures of these putative proteins were also modeled through Alphafold2. Although a portion of this workflow has previously been demonstrated to annotate hypothetical proteins from whole genome sequences, the adaptation of such steps is yet to be done for library construction purposes. We also demonstrated further downstream steps that allow a more accurate function prediction of the hypothetical proteins by subjecting the models generated to structure-based annotation. In conclusion, a total of 72 newly discovered putative proteins were annotated with ready-to-use predicted structures available for further investigation.

The Complete Genome of the “Flavescence Dorée” Phytoplasma Reveals Characteristics of Low Genome Plasticity

Members of the genus ‘Candidatus Phytoplasma’ are obligate intracellular bacteria restricted to phloem sieve elements and are able to colonize several tissues and the hemolymph in their insect vectors. The current unfeasibility of axenic culture and the low complexity of genomic sequences are obstacles in assembling complete chromosomes. Here, a method combining pathogen DNA enrichment from infected insects and dual deep-sequencing technologies was used to obtain the complete genome of a phytoplasma causing Grapevine Flavescence dorée. The de novo assembly generated a circular chromosome of 654,223 bp containing 506 protein-coding genes. Quality assessment of the draft showed a high degree of completeness. Comparative analysis with other phytoplasmas revealed the absence of potential mobile units and a reduced amount of putative phage-derived segments, suggesting a low genome plasticity. Phylogenetic analyses identified Candidatus Phytoplasma ziziphi as the closest fully sequenced relative. The “Flavescence dorée” phytoplasma strain CH genome also encoded for several putative effector proteins potentially playing a role in pathogen virulence. The availability of this genome provides the basis for the study of the pathogenicity mechanisms and evolution of the Flavescence dorée phytoplasma.

Recent Advances in the Prediction of Subcellular Localization of Proteins and Related Topics

Prediction of subcellular localization of proteins from their amino acid sequences has a long history in bioinformatics and is still actively developing, incorporating the latest advances in machine learning and proteomics. Notably, deep learning-based methods for natural language processing have made great contributions. Here, we review recent advances in the field as well as its related fields, such as subcellular proteomics and the prediction/recognition of subcellular localization from image data.

Phytoplasma effector Zaofeng6 induces shoot proliferation by decreasing the expression of ZjTCP7 in Ziziphus jujuba

The jujube witches' broom (JWB) phytoplasma is associated with witches' broom, dwarfism, and smaller leaves in jujube, resulting in yield losses. In this study, eight putative JWB effector proteins were identified from potential mobile units of the JWB genome. Among them, Zaofeng6 induced witches' broom symptoms in Arabidopsis and jujube. Zaofeng6-overexpressing Arabidopsis and unrooted jujube transformants displayed witches' broom-like shoot proliferation. Transient expression of Zaofeng6 induced hypersensitive response like cell death and expression of hypersensitive response marker genes, like harpin-induced gene 1 (H1N1), and the pathogenesis-related genes PR1, PR2, and PR3 in transformed Nicotiana benthamiana leaves, suggesting that Zaofeng6 could be a virulence effector. Yeast two-hybrid library screening and bimolecular fluorescence complementation confirmed that Zaofeng6 interacts with ZjTCP7 through its first two α-helix domains in the cell nuclei. ZjTCP7 mRNA and protein abundance decreased in Zaofeng6 transgenic jujube seedlings. The expression of some genes in the strigolactone signaling pathway (ZjCCD7, ZjCCD8, and CYP711A1) were down-regulated in jujube shoots overexpressing Zaofeng6 and in zjtcp7 CRISPR/Cas9 mutants. Zaofeng6 induces shoot proliferation through decreased expression of ZjTCP7 at the transcriptional and translational levels.

In silico high throughput mutagenesis and screening of signal peptides to mitigate N-terminal heterogeneity of recombinant monoclonal antibodies

N-terminal heterogeneity resulting from non-uniform signal peptide (SP) cleavage can potentially affect biologics property attributes and result in extended product development timelines. Few studies are available on engineering SPs systematically to address miscleavage issues. Herein, we developed a novel high throughput computational pipeline capable of generating millions of SP mutant sequences that uses the SignalP 5.0 deep learning model to predict which of these mutants are likely to alleviate the N-terminal miscleavage in antibodies. We optimized the parameters to target mutating one or two amino acids at the C-terminus of 84 unique SPs, exhausting all theoretically possible combinations and resulting in a library of 296,077 unique wildtype and mutant signal peptides for in silico screening of each antibody. We applied this method to five antibodies against different targets, with various extent of miscleavage (2.3% to 100%) on their Lambda light chains. In each case, multiple SP mutants were generated, with miscleavage reduced to a non-detectable level and titers comparable with or better than that of the original SPs. Pairwise mutational analysis using an in silico library enriched with high-scoring mutants revealed patterns of amino acids at the C-terminus of SPs, providing insights beyond the “Heijne rule”. To our knowledge, no similar approach that combines high throughput in silico mutagenesis and screening with SP cleavage prediction has been reported in the literature. This method can be applied to both the light chain and heavy chain of antibodies, regardless of their initial extent of miscleavage, provides optimized solutions for individual cases, and facilitates the development of antibody therapeutics.

Abbreviations: Aa, amino acids; CHO, Chinese hamster ovary; CNN, convolutional neural network; CSscore, cleavage site score; CSV, comma-separated values; HC, heavy chain; HEK, human embryonic kidney; HPLC, high-performance liquid chromatography; IgG, immunoglobulin G; IGLV, immunoglobulin G Lambda variable; LC, light chain; LCMS, liquid chromatography–mass spectrometry; MS, mass spectrometry; PCR, polymerase chain reaction; PBS, phosphate-buffered saline; PEI, polyethylenimine; SP, signal peptide; SPase, signal peptidase; TCEP, tris(2-carboxyethyl) phosphine; TOF, time-of-flight.

Accelerating Complete Phytoplasma Genome Assembly by Immunoprecipitation-Based Enrichment and MinION-Based DNA Sequencing for Comparative Analyses

Phytoplasmas are uncultivated plant-pathogenic bacteria with agricultural importance. Those belonging to the 16SrII group, represented by 'Candidatus P. aurantifolia', have a wide range of plant hosts and cause significant yield losses in valuable crops, such as pear, sweet potato, peanut, and soybean. In this study, a method that combines immunoprecipitation-based enrichment and MinION long-read DNA sequencing was developed to solve the challenge of phytoplasma genome studies. This approach produced long reads with high mapping rates and high genomic coverage that can be combined with Illumina reads to produce complete genome assemblies with high accuracy. We applied this method to strain NCHU2014 and determined its complete genome sequence, which consists of one circular chromosome with 635,584 bp and one plasmid with 4,224 bp. Although 'Ca. P. aurantifolia' NCHU2014 has a small chromosome with only 471 protein-coding genes, it contains 33 transporter genes and 27 putative effector genes, which may contribute to obtaining nutrients from hosts and manipulating host developments for their survival and multiplication. Two effectors, the homologs of SAP11 and SAP54/PHYL1 identified in 'Ca. P. aurantifolia' NCHU2014, have the biochemical activities in destabilizing host transcription factors, which can explain the disease symptoms observed in infected plants. Taken together, this study provides the first complete genome available for the 16SrII phytoplasmas and contributes to the understanding of phytoplasma pathogenicity.