YLoc--an interpretable web server for predicting subcellular localization

Genome-Wide Characterization of ABC Transporter Genes and Expression Profiles in Red Macroalga Pyropia yezoensis Expose to Low-Temperature

Pyropia yezoensis is an important economic macroalga widely cultivated in the East Asia countries of China, Korea, and Japan. The ATP-binding cassette (ABC) transporter gene family is one of the largest transporter families in all forms of life involved in various biological processes. The characteristics of ABC transporter genes in P. yezoensis (PyABC) and their functions in stress resistance, however, remain largely unknown. In this study, PyABCs were identified and characterized their expression patterns under low-temperature stress. A total of 48 PyABCs transporters were identified and divided into eight subfamilies, which are mostly predicted as membrane-binding proteins. The cis-elements of phytohormone and low-temperature response were distinguished in promoter sequences of PyABCs. Transcriptome analysis showed that PyABCs are involved in response to low-temperature stress. Among them, 12 PyABCs were significantly up-regulated after 24 h of exposure to low temperature (2 °C). Further quantitative RT-PCR analysis corroborated the highest expression happened at 24 for detected genes of PyABCC8, PyABCF3, and PyABCI1, extraordinarily for PyABCF3, and followed by decreased expression at 48 h. The expression of PyABCI1 was generally low in all tested strains. Whereas, in a strain of P. yezoensis with lower tolerance to low temperature, the expression was observed higher in PyABCC1, PyABCC8, and remarkably high in PyABCF3. This study provided valuable information on ABC gene families in P. yezoensis and their functional characteristics, especially on low-temperature resistance, and would help to understand the adaptive mechanisms of P. yezoensis to adverse environments.

Arbuscular mycorrhizal fungi alter carbon metabolism and invertase genes expressions of Populus simonii × P. nigra under drought stress

Arbuscular mycorrhizal fungi (AMF) play a crucial role in regulating the allocation of carbon between source and sink tissues in plants and in regulating their stress responses by changing the sucrose biosynthesis, transportation, and catabolism in plants. Invertase, a key enzyme for plant development, participates in the response of plants to drought stress by regulating sucrose metabolism. However, the detailed mechanisms by which INV genes respond to drought stress in mycorrhizal plants remain unclear. This study examined the sugar content, enzyme activity, and expression profiles of INV genes of Populus simonii × P. nigra (PsnINVs) under two inoculation treatments (inoculation or non-inoculation) and two water conditions (well-watered or drought stress). Results showed that under drought stress, AMF up-regulated the expressions of PsnA/NINV1, PsnA/NINV2, PsnA/NINV3, and PsnA/NINV5 in leaves, which may be related to the enhancement of photosynthetic capacity. Additionally, AMF up-regulated the expressions of PsnA/NINV6, PsnA/NINV10, and PsnA/NINV12 in leaves, which may be related to enhancing osmotic regulation ability and drought tolerance.

Differentially localized protein identification for breast cancer based on deep learning in immunohistochemical images

The mislocalization of proteins leads to breast cancer, one of the world's most prevalent cancers, which can be identified from immunohistochemical images. Here, based on the deep learning framework, location prediction models were constructed using the features of breast immunohistochemical images. Ultimately, six differentially localized proteins that with stable differentially predictive localization, maximum localization differences, and whose predicted results are not affected by removing a single image are obtained (CCNT1, NSUN5, PRPF4, RECQL4, UTP6, ZNF500). Further verification reveals that these proteins are not differentially expressed, but are closely associated with breast cancer and have great classification performance. Potential mechanism analysis shows that their co-expressed or co-located proteins and RNAs may affect their localization, leading to changes in interactions and functions that further causes breast cancer. They have the potential to help shed light on the molecular mechanisms of breast cancer and provide assistance for its early diagnosis and treatment.

Benzoxazinoids Biosynthetic Gene Cluster Identification and Expression Analysis in Maize under Biotic and Abiotic Stresses

Benzoxazinoids (BXs) are unique bioactive metabolites with protective and allelopathic properties in maize in response to diverse stresses. The production of BXs involves the fine regulations of BXs biosynthetic gene cluster (BGC). However, little is known about whether and how the expression pattern of BGC members is impacted by biotic and abiotic stresses. Here, maize BGC was systemically investigated and 26 BGC gene members were identified on seven chromosomes, for which Bin 4.00-4.01/4.03-4.04/7.02 were the most enriched regions. All BX proteins were clearly divided into three classes and seven subclasses, and ten conserved motifs were further identified among these proteins. These proteins were localized in the subcellular compartments of chloroplast, endoplasmic reticulum, or cytoplasmic, where their catalytic activities were specifically executed. Three independent RNA-sequencing (RNA-Seq) analyses revealed that the expression profiles of the majority of BGC gene members were distinctly affected by multiple treatments, including light spectral quality, low-temperature, 24-epibrassinolide induction, and Asian corn borer infestation. Thirteen differentially expressed genes (DEGs) with high and specific expression levels were commonly detected among three RNA-Seq, as core conserved BGC members for regulating BXs biosynthesis under multiple abiotic/biotic stimulates. Moreover, the quantitative real-time PCR (qRT-PCR) verified that six core conserved genes in BGC were significantly differentially expressed in leaves of seedlings upon four treatments, which caused significant increases in 2,4-dihydroxy-7-methoxy-1,4-benzoxazin-3-one (DIMBOA) content under darkness and wound treatments, whereas a clear decrease in DIMBOA content was observed under low-temperature treatment. In conclusion, the changes in BX metabolites in maize were regulated by BGC gene members in multiple stress presences. Therefore, the identification of key genes associated with BX accumulation under biotic/abiotic stresses will provide valuable gene resources for breeding maize varieties with enhanced capability to adapt to environmental stresses.

Subcellular Localization of Thioredoxin/Thioredoxin Reductase System-A Missing Link in Endoplasmic Reticulum Redox Balance

The lumen of the endoplasmic reticulum (ER) is usually considered an oxidative environment; however, oxidized thiol-disulfides and reduced pyridine nucleotides occur there parallelly, indicating that the ER lumen lacks components which connect the two systems. Here, we investigated the luminal presence of the thioredoxin (Trx)/thioredoxin reductase (TrxR) proteins, capable of linking the protein thiol and pyridine nucleotide pools in different compartments. It was shown that specific activity of TrxR in the ER is undetectable, whereas higher activities were measured in the cytoplasm and mitochondria. None of the Trx/TrxR isoforms were expressed in the ER by Western blot analysis. Co-localization studies of various isoforms of Trx and TrxR with ER marker Grp94 by immunofluorescent analysis further confirmed their absence from the lumen. The probability of luminal localization of each isoform was also predicted to be very low by several in silico analysis tools. ER-targeted transient transfection of HeLa cells with Trx1 and TrxR1 significantly decreased cell viability and induced apoptotic cell death. In conclusion, the absence of this electron transfer chain may explain the uncoupling of the redox systems in the ER lumen, allowing parallel presence of a reduced pyridine nucleotide and a probably oxidized protein pool necessary for cellular viability.

DNAJ protein gene expansion mechanism in Panicoideae and PgDNAJ functional identification in pearl millet

KEY MESSAGE

Analyze the evolutionary pattern of DNAJ protein genes in the Panicoideae, including pearl millet, to identify and characterize the biological function of PgDNAJ genes in pearl millet. Global warming has become a major factor threatening food security and human development. It is urgent to analyze the heat-tolerant mechanism of plants and cultivate crops that are adapted to high temperature conditions. The Panicoideae are the second largest subfamily of the Poaceae, widely distributed in warm temperate and tropical regions. Many of these species have been reported to have strong adaptability to high temperature stress, such as pearl millet, foxtail millet and sorghum. The evolutionary differences in DNAJ protein genes among 12 Panicoideae species and 10 other species were identified and analyzed. Among them, 79% of Panicoideae DNAJ protein genes were associated with retrotransposon insertion. Analysis of the DNAJ protein pan-gene family in six pearl millet accessions revealed that the non-core genes contained significantly more TEs than the core genes. By identifying and analyzing the distribution and types of TEs near the DNAJ protein genes, it was found that the insertion of Copia and Gypsy retrotransposons provided the source of expansion for the DNAJ protein genes in the Panicoideae. Based on the analysis of the evolutionary pattern of DNAJ protein genes in Panicoideae, the PgDNAJ was obtained from pearl millet through identification. PgDNAJ reduces the accumulation of reactive oxygen species caused by high temperature by activating ascorbate peroxidase (APX), thereby improving the heat resistance of plants. In summary, these data provide new ideas for mining potential heat-tolerant genes in Panicoideae, and help to improve the heat tolerance of other crops.

Like mother like son: Transgenerational memory and cross-tolerance from drought to heat stress are identified in chloroplast proteome and seed provisioning in Pinus radiata

How different stressors impact plant health and memory when they are imposed in different generations in wild ecosystems is still scarce. Here, we address how different environments shape heritable memory for the next generation in seeds and seedlings of Pinus radiata, a long-lived species with economic interest. The performance of the seedlings belonging to two wild clonal subpopulations (optimal fertirrigation vs. slightly stressful conditions) was tested under heat stress through physiological profiling and comparative time-series chloroplast proteomics. In addition, we explored the seeds conducting a physiological characterization and targeted transcriptomic profiling in both subpopulations. Our results showed differential responses between them, evidencing a cross-stress transgenerational memory. Seedlings belonging to the stressed subpopulation retained key proteins related to Photosystem II, chloroplast-to-nucleus signalling and osmoprotection which helped to overcome the applied heat stress. The seeds also showed a differential gene expression profile for targeted genes and microRNAs, as well as an increased content of starch and secondary metabolites, molecules which showed potential interest as biomarkers for early selection of primed plants. Thus, these finds not only delve into transgenerational cross-stress memory in trees, but also provide a new biotechnological tool for forest design.

Rhizobial-induced phosphatase GmPP2C61A positively regulates soybean nodulation

Symbiotic nitrogen fixation (SNF) is crucial for legumes, providing them with the nitrogen necessary for plant growth and development. Nodulation is the first step in the establishment of SNF. However, the determinant genes in soybean nodulation and the understanding of the underlying molecular mechanisms governing nodulation are still limited. Herein, we identified a phosphatase, GmPP2C61A, which was specifically induced by rhizobia inoculation. Using transgenic hairy roots harboring GmPP2C61A::GUS, we showed that GmPP2C61A was mainly induced in epidermal cells following rhizobia inoculation. Functional analysis revealed that knockdown or knock-out of GmPP2C61A significantly reduced the number of nodules, while overexpression of GmPP2C61A promoted nodule formation. Additionally, GmPP2C61A protein was mainly localized in the cytoplasm and exhibited conserved phosphatase activity in vitro. Our findings suggest that phosphatase GmPP2C61A serves as a critical regulator in soybean nodulation, highlighting its potential significance in enhancing symbiotic nitrogen fixation.

Expression of ethylene biosynthetic genes during flower senescence and in response to ethephon and silver nitrate treatments in Osmanthus fragrans

BACKGROUND

Sweet osmanthus (Osmanthus fragrans) is an ornamental evergreen tree species in China, whose flowers are sensitive to ethylene. The synthesis of ethylene is controlled by key enzymes and restriction enzymes, 1-aminocyclopropane-1-carboxylic acid synthase (ACS) and 1-aminocyclopropane-1-carboxylic acid oxidase (ACO), which are encoded by multigene families. However, the key synthase responsible for ethylene regulation in O. fragrans is still unknown.

OBJECTIVE

This study aims to screen the key ethylene synthase genes of sweet osmanthus flowers in response to ethylene regulation.

METHODS

In this study, we used the ACO and ACS sequences of Arabidopsis thaliana to search for homologous genes in the O. fragrans petal transcriptome database. These genes were also analyzed bioinformatically. Finally, the expression levels of O. fragrans were compared before and after senescence, as well as after ethephon and silver nitrate treatments.

RESULTS

The results showed that there are five ACO genes and one ACS gene in O. fragrans transcriptome database, and the phylogenetic tree revealed that the proteins encoded by these genes had high homology to the ACS and ACO proteins in plants. Sequence alignment shows that the OfACO1-5 proteins have the 2OG-Fe(II) oxygenase domain, while OfACS1 contains seven conserved domains, as well as conserved amino acids in transaminases and glutamate residues related to substrate specificity. Expression analysis revealed that the expression levels of OfACS1 and OfACO1-5 were significantly higher at the early senescence stage compared to the full flowering stage. The transcripts of the OfACS1, OfACO2, and OfACO5 genes were upregulated by treatment with ethephon. However, out of these three genes, only OfACO2 was significantly downregulated by treatment with AgNO3.

CONCLUSION

Our study found that OfACO2 is an important synthase gene in response to ethylene regulation in sweet osmanthus, which would provide valuable data for further investigation into the mechanisms of ethylene-induced senescence in sweet osmanthus flowers.

Gossypium hirsutum gene of unknown function Gohir.A02G161000 encodes a potential transmembrane Root UVB Sensitive 4 Protein with a putative protein-protein interaction interface

A gene of unknown function, Gohir.A02G161000.1, identified in Gossypium hirsutum was studied using computational sequence and structure bioinformatics tools. The associated protein GhRUS4-A0A1U8JPV7 (UniProt A0A1U8JPV7) is predicted to be a plastid-localized, transmembrane root UVB-sensitive 4 (RUS4) protein with a newly identified potential dimerization surface. Evidence from homology and sequence conservation suggest involvement in auxin transport and pollen maturation.

Unveiling the defensive role of Snakin-3, a member of the subfamily III of Snakin/GASA peptides in potatoes

KEY MESSAGE

The first in-depth characterization of a subfamily III Snakin/GASA member was performed providing experimental evidence on promoter activity and subcellular localization and unveiling a role of potato Snakin-3 in defense Snakin/GASA proteins share 12 cysteines in conserved positions in the C-terminal region. Most of them were involved in different aspects of plant growth and development, while a small number of these peptides were reported to have antimicrobial activity or participate in abiotic stress tolerance. In potato, 18 Snakin/GASA genes were identified and classified into three groups based on phylogenetic analysis. Snakin-1 and Snakin-2 are members of subfamilies I and II, respectively, and were reported to be implicated not only in defense against pathogens but also in plant development. In this work, we present the first in-depth characterization of Snakin-3, a member of the subfamily III within the Snakin/GASA gene family of potato. Transient co-expression of Snakin-3 fused to the green fluorescent protein and organelle markers revealed that it is located in the endoplasmic reticulum. Furthermore, expression analyses via pSnakin-3::GUS transgenic plants showed GUS staining mainly in roots and vascular tissues of the stem. Moreover, GUS expression levels were increased after inoculation with Pseudomonas syringae pv. tabaci or Pectobacterium carotovorum subsp. carotovorum and also after auxin treatment mainly in roots and stems. To gain further insights into the function of Snakin-3 in planta, potato overexpressing lines were challenged against P. carotovorum subsp. carotovorum showing enhanced tolerance to this bacterial pathogen. In sum, here we report the first functional characterization of a Snakin/GASA gene from subfamily III in Solanaceae. Our findings provide experimental evidence on promoter activity and subcellular localization and reveal a role of potato Snakin-3 in plant defense.

A Genome-Wide Identification and Expression Analysis of the Casparian Strip Membrane Domain Protein-like Gene Family in Pogostemon cablin in Response to p-HBA-Induced Continuous Cropping Obstacles

Casparian strip membrane domain protein-like (CASPL) genes are key genes for the formation and regulation of the Casparian strip and play an important role in plant abiotic stress. However, little research has focused on the members, characteristics, and biological functions of the patchouli PatCASPL gene family. In this study, 156 PatCASPL genes were identified at the whole-genome level. Subcellular localization predicted that 75.6% of PatCASPL proteins reside on the cell membrane. A phylogenetic analysis categorized PatCASPL genes into five subclusters alongside Arabidopsis CASPL genes. In a cis-acting element analysis, a total of 16 different cis-elements were identified, among which the photo-responsive element was the most common in the CASPL gene family. A transcriptome analysis showed that p-hydroxybenzoic acid, an allelopathic autotoxic substance, affected the expression pattern of PatCASPLs, including a total of 27 upregulated genes and 30 down-regulated genes, suggesting that these PatCASPLs may play an important role in the regulation of patchouli continuous cropping obstacles by affecting the formation and integrity of Casparian strip bands. These results provided a theoretical basis for exploring and verifying the function of the patchouli PatCASPL gene family and its role in continuous cropping obstacles.

Phylogenomics of transcriptionally active AP2/ERF and bHLH transcription factors and study of their promoter regions in Nothapodytes nimmoniana (J.Graham) Mabb

Nothapodytes nimmoniana is a medicinally important plant producing anticancer monoterpene indole alkaloid (MIA), camptothecin (CPT). The CPT is synthesised through the strictosidine intermediate following the MIA pathway; however, transcriptional regulation of CPT pathway is still elusive in N. nimmoniana. Biosynthesis of MIA is regulated by various transcription factors (TFs) belonging to AP2/ERF, bHLH, MYB, and WRKY families. The present study identified transcriptionally active full-length 105 AP2/ERF and 68 bHLH family TFs from the N. nimmoniana. AP2/ERF TFs were divided into three subfamilies along with a soloist, while bHLH TFs were divided into 10 subfamilies according to their phylogenetic similarities. Three group IXa ERFs, Nn-ERF22, Nn-ERF29, and Nn-ERF41, one subfamily IVa TF Nn-bHLH7, and three subfamilies IIIe Nn-bHLH33, Nn-bHLH51, and Nn-bHLH52 clustered with the TFs regulating alkaloid biosynthesis in Catharanthus roseus, tomato, tobacco, and Artemisia annua. Expression of these TFs in N. nimmoniana was higher in roots, which is a primary CPT accumulating tissue. Moreover, genome skimming approach was used to reconstruct the promoter regions of candidate ERF genes to identify the cis-regulatory elements. The presence of G-boxes and other jasmonic acid-responsive elements in the promoter suggests the regulation of ERFs by bHLHs. The present study effectively generated and used genomics resource for characterisation of regulatory TFs from non-model medicinal plant.

The evolution and expansion of RWP-RK gene family improve the heat adaptability of elephant grass (Pennisetum purpureum Schum.)

BACKGROUND

Along with global warming, resulting in crop production, exacerbating the global food crisis. Therefore, it is urgent to study the mechanism of plant heat resistance. However, crop resistance genes were lost due to long-term artificial domestication. By analyzing the potential heat tolerance genes and molecular mechanisms in other wild materials, more genetic resources can be provided for improving the heat tolerance of crops. Elephant grass (Pennisetum purpureum Schum.) has strong adaptability to heat stress and contains abundant heat-resistant gene resources.

RESULTS

Through sequence structure analysis, a total of 36 RWP-RK members were identified in elephant grass. Functional analysis revealed their close association with heat stress. Four randomly selected RKDs (RKD1.1, RKD4.3, RKD6.6, and RKD8.1) were analyzed for expression, and the results showed upregulation under high temperature conditions, suggesting their active role in response to heat stress. The members of RWP-RK gene family (36 genes) in elephant grass were 2.4 times higher than that of related tropical crops, rice (15 genes) and sorghum (15 genes). The 36 RWPs of elephant grass contain 15 NLPs and 21 RKDs, and 73% of RWPs are related to WGD. Among them, combined with the DAP-seq results, it was found that RWP-RK gene family expansion could improve the heat adaptability of elephant grass by enhancing nitrogen use efficiency and peroxidase gene expression.

CONCLUSIONS

RWP-RK gene family expansion in elephant grass is closely related to thermal adaptation evolution and speciation. The RKD subgroup showed a higher responsiveness than the NLP subgroup when exposed to high temperature stress. The promoter region of the RKD subgroup contains a significant number of MeJA and ABA responsive elements, which may contribute to their positive response to heat stress. These results provided a scientific basis for analyzing the heat adaptation mechanism of elephant grass and improving the heat tolerance of other crops.

The tomato chloroplast stromal proteome compendium elucidated by leveraging a plastid protein-localization prediction Atlas

Tomato (Solanum lycopersicum) is a model species for studying fruit development, wounding, herbivory, and pathogen attack. Despite tomato's world-wide economic importance and the role of chloroplasts as metabolic hubs and integrators of environmental cues, little is known about the stromal proteome of tomato. Using a high-yielding protocol for chloroplast and stromal protein isolation, MudPIT nano-LC-MS/MS analyses, a robust in-house protein database (the Atlas) for predicting the plastid localization of tomato proteins, and rigorous selection criteria for inclusion/exclusion in the stromal proteome, we identified 1,278 proteins of the tomato stromal proteome. We provide one of the most robust stromal proteomes available to date with empirical evidence for 545 and 92 proteins not previously described for tomato plastids and the Arabidopsis stroma, respectively. The relative abundance of tomato stromal proteins was determined using the exponentially modified protein abundance index (emPAI). Comparison of the abundance of tomato and Arabidopsis stromal proteomes provided evidence for the species-specific nature of stromal protein homeostasis. The manual curation of the tomato stromal proteome classified proteins into ten functional categories resulting in an accessible compendium of tomato chloroplast proteins. After curation, only 91 proteins remained as unknown, uncharacterized or as enzymes with unknown functions. The curation of the tomato stromal proteins also indicated that tomato has a number of paralogous proteins, not present in Arabidopsis, which accumulated to different levels in chloroplasts. As some of these proteins function in key metabolic pathways or in perceiving or transmitting signals critical for plant adaptation to biotic and abiotic stress, these data suggest that tomato may modulate the bidirectional communication between chloroplasts and nuclei in a novel manner. The stromal proteome provides a fertile ground for future mechanistic studies in the field of tomato chloroplast-nuclear signaling and are foundational for our goal of elucidating the dynamics of the stromal proteome controlled by the solanaceous-specific, stromal, and wound-inducible leucine aminopeptidase A of tomato.

Characterization of Chlamydomonas voltage-gated calcium channel and its interaction with photoreceptor support VGCC modulated photobehavioral response in the green alga

Calcium (Ca2+) signaling plays a major role in regulating multiple processes in living cells. The photoreceptor potential in Chlamydomonas triggers the generation of all or no flagellar Ca2+ currents that cause membrane depolarization across the eyespot and flagella. Modulation in membrane potential causes changes in the flagellar waveform, and hence, alters the beating patterns of Chlamydomonas flagella. The rhodopsin-mediated eyespot membrane potential is generated by the photoreceptor Ca2+ current or P-current however, the flagellar Ca2+ currents are mediated by unidentified voltage-gated calcium (VGCC or CaV) and potassium channels (VGKC). The voltage-gated ion channel that associates with ChRs to generate Ca2+ influx across the flagella and its cellular distribution has not yet been identified. Here, we identified putative VGCCs from algae and predicted their novel properties through insilico analysis. We further present experimental evidence on Chlamydomonas reinhardtii VGCCs to predict their novel physiological roles. Our experimental evidences showed that CrVGCC4 localizes to the eyespot and flagella of Chlamydomonas and associates with channelrhodopsins (ChRs). Further in silico interactome analysis of CrVGCCs suggested that they putatively interact with photoreceptor proteins, calcium signaling, and intraflagellar transport components. Expression analysis indicated that these VGCCs and their putative interactors can be perturbed by light stimuli. Collectively, our data suggest that VGCCs in general, and VGCC4 in particular, might be involved in the regulation of the photobehavioral response of Chlamydomonas.

PPAR-gamma agonist pioglitazone recovers mitochondrial quality control in fibroblasts from PITRM1-deficient patients

Introduction: Biallelic variants in PITRM1 are associated with a slowly progressive syndrome characterized by intellectual disability, spinocerebellar ataxia, cognitive decline and psychosis. The pitrilysin metallopeptidase 1 (PITRM1) is a mitochondrial matrix enzyme, which digests diverse oligopeptides, including the mitochondrial targeting sequences (MTS) that are cleaved from proteins imported across the inner mitochondrial membrane by the mitochondrial processing peptidase (MPP). Mitochondrial peptidases also play a role in the maturation of Frataxin, the protein affected in Friedreich's ataxia. Recent studies in yeast indicated that the mitochondrial matrix protease Ste23, which is a homologue of the human insulin-degrading enzyme (IDE), cooperates with Cym1 (homologue of PITRM1) to ensure the proper functioning of the preprotein processing machinery. In humans, IDE could be upregulated by Peroxisome Proliferator-Activated Receptor Gamma (PPARG) agonists. Methods: We investigated preprotein processing, mitochondrial membrane potential and MTS degradation in control and patients' fibroblasts, and we evaluated the pharmacological effect of the PPARG agonist Pioglitazone on mitochondrial proteostasis. Results: We discovered that PITRM1 dysfunction results in the accumulation of MTS, leading to the disruption and dissipation of the mitochondrial membrane potential. This triggers a feedback inhibition of MPP activity, consequently impairing the processing and maturation of Frataxin. Furthermore, we found that the pharmacological stimulation of PPARG by Pioglitazone upregulates IDE and also PITRM1 protein levels restoring the presequence processing machinery and improving Frataxin maturation and mitochondrial function. Discussion: Our findings provide mechanistic insights and suggest a potential pharmacological strategy for this rare neurodegenerative mitochondrial disease.

Functional Characterization of Lycopene β- and ε-Cyclases from a Lutein-Enriched Green Microalga Chlorella sorokiniana FZU60

Lutein is a high-value carotenoid with many human health benefits. Lycopene β- and ε-cyclases (LCYB and LCYE, respectively) catalyze the cyclization of lycopene into distinct downstream branches, one of which is the lutein biosynthesis pathway, via α-carotene. Hence, LCYB and LCYE are key enzymes in lutein biosynthesis. In this study, the coding genes of two lycopene cyclases (CsLCYB and CsLCYE) of a lutein-enriched marine green microalga, Chlorella sorokiniana FZU60, were isolated and identified. A sequence analysis and computational modeling of CsLCYB and CsLCYE were performed using bioinformatics to identify the key structural domains. Further, a phylogenetic analysis revealed that CsLCYB and CsLCYE were homogeneous to the proteins of other green microalgae. Subcellular localization tests in Nicotiana benthamiana showed that CsLCYB and CsLCYE localized in chloroplasts. A pigment complementation assay in Escherichia coli revealed that CsLCYB could efficiently β-cyclize both ends of lycopene to produce β-carotene. On the other hand, CsLCYE possessed a strong ε-monocyclase activity for the production of δ-carotene and a weak ε-bicyclic activity for the production of ε-carotene. In addition, CsLCYE was able to catalyze lycopene into β-monocyclic γ-carotene and ultimately produced α-carotene with a β-ring and an ε-ring via γ-carotene or δ-carotene. Moreover, the co-expression of CsLCYB and CsLCYE in E. coli revealed that α-carotene was a major product, which might lead to the production of a high level of lutein in C. sorokiniana FZU60. The findings provide a theoretical foundation for performing metabolic engineering to improve lutein biosynthesis and accumulation in C. sorokiniana FZU60.

An Assessment of the Penile Squamous Cell Carcinoma Surfaceome for Biomarker and Therapeutic Target Discovery

Penile squamous cell carcinoma (PSCC) is a rare malignancy in most parts of the world and the underlying mechanisms of this disease have not been fully investigated. About 30-50% of cases are associated with high-risk human papillomavirus (HPV) infection, which may have prognostic value. When PSCC becomes resistant to upfront therapies there are limited options, thus further research is needed in this venue. The extracellular domain-facing protein profile on the cell surface (i.e., the surfaceome) is a key area for biomarker and drug target discovery. This research employs computational methods combined with cell line translatomic (n = 5) and RNA-seq transcriptomic data from patient-derived tumors (n = 18) to characterize the PSCC surfaceome, evaluate the composition dependency on HPV infection, and explore the prognostic impact of identified surfaceome candidates. Immunohistochemistry (IHC) was used to validate the localization of select surfaceome markers. This analysis characterized a diverse surfaceome within patient tumors with 25% and 18% of the surfaceome represented by the functional classes of receptors and transporters, respectively. Significant differences in protein classes were noted by HPV status, with the most change being seen in transporter proteins (25%). IHC confirmed the robust surface expression of select surfaceome targets in the top 85% of expression and a superfamily immunoglobulin protein called BSG/CD147 was prognostic of survival. This study provides the first description of the PSCC surfaceome and its relation to HPV infection and sets a foundation for novel biomarker and drug target discovery in this rare cancer.

Genome-wide characterization of the VQ genes in Triticeae and their functionalization driven by polyploidization and gene duplication events in wheat

Valine-glutamine motif-containing (VQ) proteins are transcriptional cofactors widely involved in plant growth, development, and response to various stresses. Although the VQ family has been genome-wide identified in some species, but the knowledge regarding duplication-driven functionalization of VQ genes among evolutionarily related species is still lacking. Here, 952 VQ genes have been identified from 16 species, emphasizing seven Triticeae species including the bread wheat. Comprehensive phylogenetic and syntenic analyses allow us to establish the orthologous relationship of VQ genes from rice (Oryza sativa) to bread wheat (Triticum aestivum). The evolutionary analysis revealed that whole-genome duplication (WGD) drives the expansion of OsVQs, while TaVQs expansion is associated with a recent burst of gene duplication (RBGD). We also analyzed the motif composition and molecular properties of TaVQ proteins, enriched biological functions, and expression patterns of TaVQs. We demonstrate that WGD-derived TaVQs have become divergent in both protein motif composition and expression pattern, while RBGD-derived TaVQs tend to adopt specific expression patterns, suggesting their functionalization in certain biological processes or in response to specific stresses. Furthermore, some RBGD-derived TaVQs are found to be associated with salt tolerance. Several of the identified salt-related TaVQ proteins were located in the cytoplasm and nucleus and their salt-responsive expression patterns were validated by qPCR analysis. Yeast-based functional experiments confirmed that TaVQ27 may be a new regulator to salt response and regulation. Overall, this study lays the foundation for further functional validation of VQ family members within the Triticeae species.

Genome-Wide Characterization and Sequence Polymorphism Analyses of Glycine max Fibrillin (FBN) Revealed Its Role in Response to Drought Condition

The fibrillin (FBN) gene family is widely distributed in all photosynthetic organisms. Members of this gene family are involved in plant growth and development and their response to various biotic and abiotic stress factors. In this study, 16 members of FBN were identified in Glycine max and characterized by using different bioinformatics tools. Phylogenetic analysis classified FBN genes into seven groups. The presence of stress-related cis-elements in the upstream region of GmFBN highlighted their role in tolerance against abiotic stresses. To further decipher the function, physiochemical properties, conserved motifs, chromosomal localization, subcellular localization, and cis-acting regulatory elements were also analyzed. Gene expression analysis based on FPKM values revealed that GmFBNs greatly enhanced soybean drought tolerance and controlled the expression of several genes involved in drought response, except for GmFBN-4, GmFBN-5, GmFBN-6, GmFBN-7 and GmFBN-9. For high throughput genotyping, an SNP-based CAPS marker was also developed for the GmFBN-15 gene. The CAPS marker differentiated soybean genotypes based on the presence of either the GmFBN-15-G or GmFBN-15-A alleles in the CDS region. Association analysis showed that G. max accessions containing the GmFBN-15-A allele at the respective locus showed higher thousand seed weight compared to accessions containing the GmFBN-15-G allele. This research has provided the basic information to further decipher the function of FBN in soybean.

Gossypium hirsutum gene of unknown function Gohir.A03G007700.1 encodes a potential VAN3-binding protein with a phosphoinositide-binding site

A gene of unknown function, Gohir.A03G007700.1 (gene ID: Gohir.A03G007700_UTX-TM1_v2.1; transcript ID: Gohir.A03G007700.1_UTX-TM1_v2.1), identified in Gossypium hirsutum was studied using bioinformatic analyses of the sequence and structure of its encoded protein. Results from domain prediction, conserved residues and structure comparison indicate the encoded plant-specific protein (UniProt A0A1U8N485) is part of the VAN3-binding protein family with a conserved phosphoinositide-binding site. Homology comparison suggests functional similarity with Arabidopsis FORKED-like FL5 and 6, which localize to the Golgi apparatus and are linked to vein development and leaf size phenotypes.

Structure based functional annotation of a MYND-less lysine methyl transferase inCandida albicans

Candida albicans is opportunistic pathogenic yeast that is widely distributed throughout the world and is classified as the most critical fungal pathogen group. Candida albicans is a common microbiota of healthy individuals but can cause superficial and invasive infections in immune compromised individuals. Protein Post-translational modifications involving methylation of lysine amino acids stand for a major regulator of eukaryotic transcription, and pathways controlling several cellular processes. SMYD makes up a SET (Su (Var) 3-9, Enhancer-of-zeste and Trithorax) and MYND (Myeloid, Nervy, and DEAF-1) domain containing lysine methyl transferase subfamily that transfers methyl groups from methyl donors onto lysine residues in histones (H3 and H4) and non-histone proteins. The SET domain is the methyltransferase catalytic domain, while MYND participates in both protein and DNA interactions. Well-studied examples of SMYD proteins are five human and two Saccharomyces cerevisiae, constituting examples of histone and non-histone protein lysine methyl transferase members. However, there is limited understanding of SET lysine methyltransferases, including the SMYD subfamily, in the pathogenic fungi Candida albicans. Using bioinformatics tools, we characterized the SMYD domain containing proteins in the important pathogen. We report the presence of an atypical SMYD member (CaO19.3863) as a new lysine methyltransferase that can be a target for antifungal therapy.

Protein Subcellular Localization Prediction Model Based on Graph Convolutional Network

Protein subcellular localization prediction is an important research area in bioinformatics, which plays an essential role in understanding protein function and mechanism. Many machine learning and deep learning algorithms have been employed for this task, but most of them do not use structural information of proteins. With the advances in protein structure research in recent years, protein contact map prediction has been dramatically enhanced. In this paper, we present GraphLoc, a deep learning model that predicts the localization of proteins at the subcellular level. The cores of the model are a graph convolutional neural network module and a multi-head attention module. The protein topology graph is constructed based on a contact map predicted from protein sequences, which is used as the input of the GCN module to take full advantage of the structural information of proteins. Multi-head attention module learns the weighted contribution of different amino acids to subcellular localization in different feature representation subspaces. Experiments on the benchmark dataset show that the performance of our model is better than others. The code can be accessed at https://github.com/GoodGuy398/GraphLoc . The proposed GraphLoc model consists of three parts. The first part is a graph convolutional network (GCN) module, which utilizes the predicted contact maps to construct protein graph, taking benefit of protein information accordingly. The second part is the multi-head attention module, which learns the weighted contribution of different amino acids in different feature representation subspace, and weighted average the feature map across all amino acid nodes. The last part is a fully connected layer that maps the flatten graph representation vector to another vector with a category number dimension, followed by a softmax layer to predict the protein subcellular localization.

Predictive modeling of moonlighting DNA-binding proteins

Moonlighting proteins are multifunctional, single-polypeptide chains capable of performing multiple autonomous functions. Most moonlighting proteins have been discovered through work unrelated to their multifunctionality. We believe that prediction of moonlighting proteins from first principles, that is, using sequence, predicted structure, evolutionary profiles, and global gene expression profiles, for only one functional class of proteins in a single organism at a time will significantly advance our understanding of multifunctional proteins. In this work, we investigated human moonlighting DNA-binding proteins (mDBPs) in terms of properties that distinguish them from other (non-moonlighting) proteins with the same DNA-binding protein (DBP) function. Following a careful and comprehensive analysis of discriminatory features, a machine learning model was developed to assess the predictability of mDBPs from other DBPs (oDBPs). We observed that mDBPs can be discriminated from oDBPs with high accuracy of 74% AUC of ROC using these first principles features. A number of novel predicted mDBPs were found to have literature support for their being moonlighting and others are proposed as candidates, for which the moonlighting function is currently unknown. We believe that this work will help in deciphering and annotating novel moonlighting DBPs and scale up other functions. The source codes and data sets used for this work are freely available at https://zenodo.org/record/7299265#.Y2pO3ctBxPY.

Analysis of nested alternate open reading frames and their encoded proteins

Transcriptional and post-transcriptional mechanisms diversify the proteome beyond gene number, while maintaining a sequence relationship between original and altered proteins. A new mechanism breaks this paradigm, generating novel proteins by translating alternative open reading frames (Alt-ORFs) within canonical host mRNAs. Uniquely, ‘alt-proteins’ lack sequence homology with host ORF-derived proteins. We show global amino acid frequencies, and consequent biochemical characteristics of Alt-ORFs nested within host ORFs (nAlt-ORFs), are genetically-driven, and predicted by summation of frequencies of hundreds of encompassing host codon-pairs. Analysis of 101 human nAlt-ORFs of length ≥150 codons confirms the theoretical predictions, revealing an extraordinarily high median isoelectric point (pI) of 11.68, due to anomalous charged amino acid levels. Also, nAlt-ORF proteins exhibit a >2-fold preference for reading frame 2 versus 3, predicted mitochondrial and nuclear localization, and elevated codon adaptation index indicative of natural selection. Our results provide a theoretical and conceptual framework for exploration of these largely unannotated, but potentially significant, alternative ORFs and their encoded proteins.

Genome-wide identification and characterization of NPF family reveals NtNPF6.13 involving in salt stress in Nicotiana tabacum

Proteins of the Nitrate Transporter 1/Peptide Transporter (NPF) family transport a diverse variety of substrates, such as nitrate, peptides, hormones and chloride. In this study, a systematic analysis of the tobacco (Nicotiana tabacum) NPF family was performed in the cultivated 'K326'. In total, 143 NtNPF genes were identified and phylogenetically classified into eight subfamilies, NPF1 to NPF8, based on the classification of NPF families in other plant species. The chromosomal locations and structures of the NtNPF genes were analyzed. The expression profiles of NtNPF genes under NaCl stress were analyzed to screen the possible NPF genes involving in chloride regulation in tobacco. Most NtNPF6 genes responded to salt stress in the roots and leaves. The expression of NtNPF6.13 was significantly down-regulated after salt stress for 12h. The chloride content was reduced in the roots of ntnpf6.13 mutant. These findings support the participation of NtNPF6.13 in chloride uptake. Several other NtNPF genes that play potential roles in chloride metabolism of tobacco require further study.

An Integrated Proteomic Strategy to Identify SHP2 Substrates

Protein phosphatases play an essential role in normal cell physiology and the development of diseases such as cancer. The innate challenges associated with studying protein phosphatases have limited our understanding of their substrates, molecular mechanisms, and unique functions within highly coordinated networks. Here, we introduce a novel strategy using substrate-trapping mutants coupled with quantitative proteomics methods to identify physiological substrates of Src homology 2 containing protein tyrosine phosphatase 2 (SHP2) in a high-throughput manner. The technique integrates three parallel mass spectrometry-based proteomics experiments, including affinity isolation of substrate-trapping mutant complex using wild-type and SHP2 KO cells, in vivo global quantitative phosphoproteomics, and in vitro phosphatase reaction. We confidently identified 18 direct substrates of SHP2 in the epidermal growth factor receptor signaling pathways, including both known and novel SHP2 substrates. Docking protein 1 was further validated using biochemical assays as a novel SHP2 substrate, providing a mechanism for SHP2-mediated Ras activation. This advanced workflow improves the systemic identification of direct substrates of protein phosphatases, facilitating our understanding of the equally important roles of protein phosphatases in cellular signaling.

SLPred: a multi-view subcellular localization prediction tool for multi-location human proteins

SUMMARY

Accurate prediction of the subcellular locations (SLs) of proteins is a critical topic in protein science. In this study, we present SLPred, an ensemble-based multi-view and multi-label protein subcellular localization prediction tool. For a query protein sequence, SLPred provides predictions for nine main SLs using independent machine-learning models trained for each location. We used UniProtKB/Swiss-Prot human protein entries and their curated SL annotations as our source data. We connected all disjoint terms in the UniProt SL hierarchy based on the corresponding term relationships in the cellular component category of Gene Ontology and constructed a training dataset that is both reliable and large scale using the re-organized hierarchy. We tested SLPred on multiple benchmarking datasets including our-in house sets and compared its performance against six state-of-the-art methods. Results indicated that SLPred outperforms other tools in the majority of cases.

AVAILABILITY AND IMPLEMENTATION

SLPred is available both as an open-access and user-friendly web-server (https://slpred.kansil.org) and a stand-alone tool (https://github.com/kansil/SLPred). All datasets used in this study are also available at https://slpred.kansil.org.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Understanding the Role of Nitronate Monooxygenases in Virulence of the Human Fungal Pathogen Aspergillus fumigatus

Aspergillus fumigatus is the leading cause of the fungal invasive disease called aspergillosis, which is associated with a high mortality rate that can reach 50% in some groups of immunocompromised individuals. The increasing prevalence of azole-resistant A. fumigatus isolates, both in clinical settings and the environment, highlights the importance of discovering new fungal virulence factors that can potentially become targets for novel antifungals. Nitronate monooxygenases (Nmos) represent potential targets for antifungal compounds as no orthologs of those enzymes are present in humans. Nmos catalyse the denitrification of nitroalkanes, thereby detoxifying these mediators of nitro-oxidative stress, and therefore we tested whether Nmos provide protection for A. fumigatus against host-imposed stresses at sites of infection. The results of inhibition zone assays indicated that Nmo2 and Nmo5 are not essential for the oxidative stress resistance of A. fumigatus in vitro. In addition, the resazurin-based metabolic activity assay revealed that the growth of mutants lacking the nmo2 or nmo5 genes was only slightly reduced in the presence of 0.05 mM peroxynitrite. Nevertheless, both Nmo2 and Nmo5 were shown to contribute to defense against murine bone marrow-derived macrophages, and this was no longer observed when NADPH oxidase, the main generator of reactive oxygen species during infection, was inhibited in macrophages. Furthermore, we revealed that Nnmos promote the virulence of the fungus in the Galleria mellonella model of infection. Both nmo2 and nmo5 knock-out strains were less virulent than the wild-type control as recorded 72 h post-infection. Our results indicate that Nmos play a role in the virulence of A. fumigatus.

Multiple Protein Subcellular Locations Prediction Based on Deep Convolutional Neural Networks with Self-Attention Mechanism

As an important research field in bioinformatics, protein subcellular location prediction is critical to reveal the protein functions and provide insightful information for disease diagnosis and drug development. Predicting protein subcellular locations remains a challenging task due to the difficulty of finding representative features and robust classifiers. Many feature fusion methods have been widely applied to tackle the above issues. However, they still suffer from accuracy loss due to feature redundancy. Furthermore, multiple protein subcellular locations prediction is more complicated since it is fundamentally a multi-label classification problem. The traditional binary classifiers or even multi-class classifiers cannot achieve satisfactory results. This paper proposes a novel method for protein subcellular location prediction with both single and multiple sites based on deep convolutional neural networks. Specifically, we first obtain the integrated features by simultaneously considering the pseudo amino acid, amino acid index distribution, and physicochemical property. We then adopt deep convolutional neural networks to extract high-dimensional features from the fused feature, removing the redundant preliminary features and gaining better representations of the raw sequences. Moreover, we use the self-attention mechanism and a customized loss function to ensure that the model is more inclined to positive data. In addition, we use random k-label sets to reduce the number of prediction labels. Meanwhile, we employ a hybrid strategy of over-sampling and under-sampling to tackle the data imbalance problem. We compare our model with three representative classification alternatives. The experiment results show that our model achieves the best performance in terms of accuracy, demonstrating the efficacy of the proposed model.

Genome-Wide Identification and Analysis of Heat Shock Protein 70 Family in Theobroma cacao

<b>Background and Objective:</b> In plants, the 70 kDa heat shock proteins (Hsp70-s) play important roles during growth and development and in response to stresses. This study aimed to provide comprehensive information on the <i>Hsp70 </i>family in cocoa (<i>Theobroma cacao</i>), one of the most important tropical perennial cash crops worldwide. <b>Materials and Methods:</b> A basic local alignment search tool (TBLASTN) against the cocoa genome was performed using <i>Arabidopsis</i> Hsp70-s as queries to detect TcHsp70-s. Sequence analyses were carried out by various bioinformatics tools. <b>Results:</b> A total of 18 members of the <i>Hsp70</i> family has been detected and characterized in the cocoa genome. All general properties, such as physic-chemical parameters, gene structure, phylogenetic tree and sub-cellular localization, were determined using a variety of bioinformatics tools. The expression patterns of the <i>TcHsp70</i> genes in different stages of the zygotic and somatic embryos were investigated. In addition, expression profiles of the <i>TcHsp70</i> genes under <i>Phytophthora megakarya</i> inoculation were analyzed. <b>Conclusion:</b> The results of this study revealed the features and expression analyses of <i>Hsp70</i> genes in cocoa. These findings could provide a strong foundation for further research of the <i>TcHsp70</i> family, which could aid in the development and stress tolerance of cocoa species.

Genome-Wide Analyses of Aspartic Proteases on Potato Genome (Solanum tuberosum): Generating New Tools to Improve the Resistance of Plants to Abiotic Stress

Aspartic proteases are proteolytic enzymes widely distributed in living organisms and viruses. Although they have been extensively studied in many plant species, they are poorly described in potatoes. The present study aimed to identify and characterize S. tuberosum aspartic proteases. Gene structure, chromosome and protein domain organization, phylogeny, and subcellular predicted localization were analyzed and integrated with RNAseq data from different tissues, organs, and conditions focused on abiotic stress. Sixty-two aspartic protease genes were retrieved from the potato genome, distributed in 12 chromosomes. A high number of intronless genes and segmental and tandem duplications were detected. Phylogenetic analysis revealed eight StAP groups, named from StAPI to StAPVIII, that were differentiated into typical (StAPI), nucellin-like (StAPIIIa), and atypical aspartic proteases (StAPII, StAPIIIb to StAPVIII). RNAseq data analyses showed that gene expression was consistent with the presence of cis-acting regulatory elements on StAP promoter regions related to water deficit. The study presents the first identification and characterization of 62 aspartic protease genes and proteins on the potato genome and provides the baseline material for functional gene determinations and potato breeding programs, including gene editing mediated by CRISPR.

SIFLoc: a self-supervised pre-training method for enhancing the recognition of protein subcellular localization in immunofluorescence microscopic images

With the rapid growth of high-resolution microscopy imaging data, revealing the subcellular map of human proteins has become a central task in the spatial proteome. The cell atlas of the Human Protein Atlas (HPA) provides precious resources for recognizing subcellular localization patterns at the cell level, and the large-scale annotated data enable learning via advanced deep neural networks. However, the existing predictors still suffer from the imbalanced class distribution and the lack of labeled data for minor classes. Thus, it is necessary to develop new methods for coping with these issues. We leverage the self-supervised learning protocol to address these problems. Especially, we propose a pre-training scheme to enhance the conventional supervised learning framework called SIFLoc. The pre-training is featured by a hybrid data augmentation method and a modified contrastive loss function, aiming to learn good feature representations from microscopic images. The experiments are performed on a large-scale immunofluorescence microscopic image dataset collected from the HPA database. Using the same deep neural networks as the classifier, the model pre-trained via SIFLoc not only outperforms the model without pre-training by a large margin but also shows advantages over the state-of-the-art self-supervised learning methods. Especially, SIFLoc improves the prediction accuracy for minor organelles significantly.

ProtPlat: an efficient pre-training platform for protein classification based on FastText

Background

For the past decades, benefitting from the rapid growth of protein sequence data in public databases, a lot of machine learning methods have been developed to predict physicochemical properties or functions of proteins using amino acid sequence features. However, the prediction performance often suffers from the lack of labeled data. In recent years, pre-training methods have been widely studied to address the small-sample issue in computer vision and natural language processing fields, while specific pre-training techniques for protein sequences are few.

Results

In this paper, we propose a pre-training platform for representing protein sequences, called ProtPlat, which uses the Pfam database to train a three-layer neural network, and then uses specific training data from downstream tasks to fine-tune the model. ProtPlat can learn good representations for amino acids, and at the same time achieve efficient classification. We conduct experiments on three protein classification tasks, including the identification of type III secreted effectors, the prediction of subcellular localization, and the recognition of signal peptides. The experimental results show that the pre-training can enhance model performance effectively and ProtPlat is competitive to the state-of-the-art predictors, especially for small datasets. We implement the ProtPlat platform as a web service (https://compbio.sjtu.edu.cn/protplat) that is accessible to the public.

Conclusions

To enhance the feature representation of protein amino acid sequences and improve the performance of sequence-based classification tasks, we develop ProtPlat, a general platform for the pre-training of protein sequences, which is featured by a large-scale supervised training based on Pfam database and an efficient learning model, FastText. The experimental results of three downstream classification tasks demonstrate the efficacy of ProtPlat.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-022-04604-2.

Subcellular Proteomics as a Unified Approach of Experimental Localizations and Computed Prediction Data for Arabidopsis and Crop Plants

In eukaryotic organisms, subcellular protein location is critical in defining protein function and understanding sub-functionalization of gene families. Some proteins have defined locations, whereas others have low specificity targeting and complex accumulation patterns. There is no single approach that can be considered entirely adequate for defining the in vivo location of all proteins. By combining evidence from different approaches, the strengths and weaknesses of different technologies can be estimated, and a location consensus can be built. The Subcellular Location of Proteins in Arabidopsis database ( http://suba.live/ ) combines experimental data sets that have been reported in the literature and is analyzing these data to provide useful tools for biologists to interpret their own data. Foremost among these tools is a consensus classifier (SUBAcon) that computes a proposed location for all proteins based on balancing the experimental evidence and predictions. Further tools analyze sets of proteins to define the abundance of cellular structures. Extending these types of resources to plant crop species has been complex due to polyploidy, gene family expansion and contraction, and the movement of pathways and processes within cells across the plant kingdom. The Crop Proteins of Annotated Location database ( http://crop-pal.org/ ) has developed a range of subcellular location resources including a species-specific voting consensus for 12 plant crop species that offers collated evidence and filters for current crop proteomes akin to SUBA. Comprehensive cross-species comparison of these data shows that the sub-cellular proteomes (subcellulomes) depend only to some degree on phylogenetic relationship and are more conserved in major biosynthesis than in metabolic pathways. Together SUBA and cropPAL created reference subcellulomes for plants as well as species-specific subcellulomes for cross-species data mining. These data collections are increasingly used by the research community to provide a subcellular protein location layer, inform models of compartmented cell function and protein-protein interaction network, guide future molecular crop breeding strategies, or simply answer a specific question-where is my protein of interest inside the cell?

Nucleus and chloroplast: A necessary understanding to overcome heat stress in Pinus radiata

The recovery and maintenance of plant homeostasis under stressful environments are complex processes involving organelle crosstalk for a coordinated cellular response. Here, we revealed through nuclear and chloroplast subcellular proteomics, biochemical cell profiles and targeted transcriptomics how chloroplasts and nuclei developed their responses under increased temperatures in a long-lived species (Pinus radiata). Parallel to photosynthetic impairment and reactive oxygen species production in the chloroplast, a DNA damage response was triggered in the nucleus followed by an altered chromatin conformation. In addition, in the nuclei, we found several proteins, such as HEMERA or WHIRLY, which change their locations from the chloroplasts to the nuclei carrying the stress message. Additionally, our data showed a deep rearrangement of RNA metabolism in both organelles, revealing microRNAs and AGO1 as potential regulators of the acclimation mechanisms. Altogether, our study highlights the synchronisation among the different stages required for thermotolerance acquisition in P. radiata, pointing out the role of chromatin conformation and posttranscriptional gene regulation in overcoming heat stress and assuring plant survival for the following years.

SWEET Gene Family in Sugar Beet (Beta vulgaris): Genome-Wide Survey, Phylogeny and Expression Analysis

<b>Background and Objective:</b> The SWEET (Sugars Will Eventually be Exported Transporter) proteins play important roles in modulating the growth and development processes in plants. However, little information is available on the SWEET family in sugar beet (<i>Beta vulgaris</i>). The objectives of this present study were to genome-wide identify and characterize the BvSWEET family in sugar beet. <b>Materials and Methods:</b> Based on the available genome, proteome and transcriptome databases of sugar beet, various computational tools have been used to analyze the nucleotide and full-length protein sequences of members of the BvSWEET family. <b>Results:</b> A total of 16 members of the BvSWEET family has been identified in sugar beet at the genome-wide scale. Structural analysis indicated that the BvSWEET family exhibited variable characteristics. Furthermore, the BvSWEET family in sugar beet could be categorized into four distinct groups like in other plant species. Of our interest, we found that some <i>BvSWEET</i> genes exhibited strongly preferential expression in major organs/tissues under adverse environmental stimuli. <b>Conclusion:</b> The results provided a comprehensive foundation for further functional characterization of the <i>BvSWEET </i>gene family.

Genome-Wide Identification and Expression Analysis of the R2R3-MYB Transcription Factor Family Revealed Their Potential Roles in the Flowering Process in Longan (Dimocarpus longan)

Longan (Dimocarpus longan Lour.) is a productive fruit crop with high nutritional and medical value in tropical and subtropical regions. The MYB gene family is one of the most widespread plant transcription factor (TF) families participating in the flowering regulation. However, little is known about the MYB TFs involved in the flowering process in longan and its regulatory network. In this study, a total of 119 DlR2R3-MYB genes were identified in the longan genome and were phylogenetically grouped into 28 subgroups. The groupings were supported by highly conserved gene structures and motif composition of DlR2R3-MYB genes in each subgroup. Collinearity analysis demonstrated that segmental replications played a more crucial role in the expansion of the DlR2R3-MYB gene family compared to tandem duplications, and all tandem/segmental duplication gene pairs have evolved under purifying selection. Interspecies synteny analysis among longan and five representative species implied the occurrence of gene duplication events was one of the reasons contributing to functional differentiation among species. RNA-seq data from various tissues showed DlR2R3-MYB genes displayed tissue-preferential expression patterns. The pathway of flower development was enriched with six DlR2R3-MYB genes. Cis-acting element prediction revealed the putative functions of DlR2R3-MYB genes were related to the plant development, phytohormones, and environmental stresses. Notably, the orthologous counterparts between Arabidopsis and longan R2R3-MYB members tended to play conserved roles in the flowering regulation and stress responses. Transcriptome profiling on off-season flower induction (FI) by KClO₃ indicated two up-regulated and four down-regulated DlR2R3-MYB genes involved in the response to KClO₃ treatment compared with control groups. Additionally, qRT-PCR confirmed certain genes exhibited high expression in flowers/flower buds. Subcellular localization experiments revealed that three predicted flowering-associated MYB proteins were localized in the nucleus. Future functional studies on these potential candidate genes involved in the flowering development could further the understanding of the flowering regulation mechanism.

Heat Shock Protein 20 Gene Superfamilies in Red Algae: Evolutionary and Functional Diversities

Heat shock protein 20 (Hsp20) genes play important roles in plant growth, development, and response to environmental stress. However, the Hsp20 gene family has not yet been systematically investigated, and its function in red algae (Rhodophyta) remains poorly understood. Herein, we characterized Hsp20 gene families in red algae by studying gene structure, conserved motifs, phylogenetic relationships, chromosome location, gene duplication, cis-regulatory elements, and expression profiles. In this study, 97 Hsp20 genes were identified using bioinformatic methods and classified into 13 subfamilies based on phylogenetic relationships. Phylogenetic analysis revealed that Hsp20 genes might have a polyphyletic origin and a complex evolutionary pattern. Gene structure analysis revealed that most Hsp20 genes possessed no introns, and all Hsp20 genes contained a conserved α-crystalline domain in the C-terminal region. Conserved motif analysis revealed that Hsp20 genes belonging to the same subfamily shared similar motifs. Gene duplication analysis demonstrated that tandem and segmental duplication events occurred in these gene families. Additionally, these gene families in red algae might have experienced strong purifying selection pressure during evolution, and Hsp20 genes in Pyropia yezoensis, Pyropia haitanensis, and Porphyra umbilicalis were highly evolutionarily conserved. The cis-elements of phytohormone-, light-, stress-responsive, and development-related were identified in the red algal Hsp20 gene promoter sequences. Finally, using Py. yezoensis, as a representative of red algae, the Hsp20 gene expression profile was explored. Based on the RNA-seq data, Py. yezoensis Hsp20 (PyyHsp20) genes were found to be involved in Py. yezoensis responses against abiotic and biotic stresses and exhibited diverse expression patterns. Moreover, PyyHsp20 is involved in Py. yezoensis growth and development and revealed spatial and temporal expression patterns. These results provide comprehensive and valuable information on Hsp20 gene families in red algae and lay a foundation for their functional characterization. In addition, our study provides new insights into the evolution of Hsp20 gene families in red algae and will help understand the adaptability of red algae to diverse environments.

Genome-wide identification and expression profiling of invertase gene family for abiotic stresses tolerance in Poncirus trifoliata

BACKGROUND

Sucrose (Suc) hydrolysis is directly associated with plants tolerance to multiple abiotic stresses. Invertase (INV) enzymes irreversibly catalyze Suc degradation to produce glucose (Glc) and fructose (Frc). However, genome-wide identification and function of individual members of the INV gene family in Poncirus trifoliata or its Citrus relatives in response to abiotic stresses are not fully understood.

RESULTS

In this report, fourteen non-redundant PtrINV family members were identified in P. trifoliata including seven alkaline/neutral INV genes (PtrA/NINV1-7), two vacuolar INV genes (PtrVINV1-2), and five cell wall INV isoforms (PtrCWINV1-5). A comprehensive analysis based on the biochemical characteristics, the chromosomal location, the exon-intron structures and the evolutionary relationships demonstrated the conservation and the divergence of PtrINVs. In addition, expression analysis of INV genes during several abiotic stresses in various tissues indicated the central role of A/NINV7 among INV family members in response to abiotic stresses. Furthermore, our data demonstrated that high accumulation of Suc, Glc, Frc and total sugar contents were directly correlated with the elevated activities of soluble INV enzymes in the cold-tolerant P. trifoliata, C. ichangensis and C. sinensis, demonstrating the potential role of soluble INV enzymes for the cold tolerance of Citrus.

CONCLUSIONS

This work offered a framework for understanding the physiological role of INV genes and laid a foundation for future functional studies of these genes in response to abiotic stresses.

Light attention predicts protein location from the language of life

Summary

Although knowing where a protein functions in a cell is important to characterize biological processes, this information remains unavailable for most known proteins. Machine learning narrows the gap through predictions from expert-designed input features leveraging information from multiple sequence alignments (MSAs) that is resource expensive to generate. Here, we showcased using embeddings from protein language models for competitive localization prediction without MSAs. Our lightweight deep neural network architecture used a softmax weighted aggregation mechanism with linear complexity in sequence length referred to as light attention. The method significantly outperformed the state-of-the-art (SOTA) for 10 localization classes by about 8 percentage points (Q10). So far, this might be the highest improvement of just embeddings over MSAs. Our new test set highlighted the limits of standard static datasets: while inviting new models, they might not suffice to claim improvements over the SOTA.

Availability and implementation

The novel models are available as a web-service at http://embed.protein.properties. Code needed to reproduce results is provided at https://github.com/HannesStark/protein-localization. Predictions for the human proteome are available at https://zenodo.org/record/5047020.

Supplementary information

Supplementary data are available at Bioinformatics Advances online.

Computational methods for protein localization prediction

The accurate annotation of protein localization is crucial in understanding protein function in tandem with a broad range of applications such as pathological analysis and drug design. Since most proteins do not have experimentally-determined localization information, the computational prediction of protein localization has been an active research area for more than two decades. In particular, recent machine-learning advancements have fueled the development of new methods in protein localization prediction. In this review paper, we first categorize the main features and algorithms used for protein localization prediction. Then, we summarize a list of protein localization prediction tools in terms of their coverage, characteristics, and accessibility to help users find suitable tools based on their needs. Next, we evaluate some of these tools on a benchmark dataset. Finally, we provide an outlook on the future exploration of protein localization methods.

GhGASA10-1 promotes the cell elongation in fiber development through the phytohormones IAA-induced

BACKGROUND

Cotton is an important cash crop. The fiber length has always been a hot spot, but multi-factor control of fiber quality makes it complex to understand its genetic basis. Previous reports suggested that OsGASR9 promotes germination, width, and thickness by GAs in rice, while the overexpression of AtGASA10 leads to reduced silique length, which is likely to reduce cell wall expansion. Therefore, this study aimed to explore the function of GhGASA10 in cotton fibers development.

RESULTS

To explore the molecular mechanisms underlying fiber elongation regulation concerning GhGASA10-1, we revealed an evolutionary basis, gene structure, and expression. Our results emphasized the conservative nature of GASA family with its origin in lower fern plants S. moellendorffii. GhGASA10-1 was localized in the cell membrane, which may synthesize and transport secreted proteins to the cell wall. Besides, GhGASA10-1 promoted seedling germination and root extension in transgenic Arabidopsis, indicating that GhGASA10-1 promotes cell elongation. Interestingly, GhGASA10-1 was upregulated by IAA at fiber elongation stages.

CONCLUSION

We propose that GhGASA10-1 may promote fiber elongation by regulating the synthesis of cellulose induced by IAA, to lay the foundation for future research on the regulation networks of GASA10-1 in cotton fiber development.

Dehydrin MsDHN1 improves aluminum tolerance of alfalfa (Medicago sativa L.) by affecting oxalate exudation from root tips

A SK3 -type dehydrin MsDHN1 was cloned from alfalfa (Medicago sativa L.). Its function and gene regulatory pathways were studied via overexpression and suppression of MsDHN1 in alfalfa seedlings or hairy roots. The results showed that MsDHN1 is a typical intrinsically disordered protein that exists in the form of monomers and homodimers in alfalfa. The plant growth rates increased as a result of MsDHN1 overexpression (MsDHN1-OE) and decreased upon MsDHN1 suppression (MsDHN1-RNAi) in seedlings or hairy roots of alfalfa compared with the wild-type or the vector line under Al stress. MsDHN1 interacting with aquaporin (AQP) MsPIP2;1 and MsTIP1;1 positively affected oxalate secretion from root tips and Al accumulation in root tips. MsABF2 was proven to be an upstream transcription factor of MsDHN1 and activated MsDHN1 expression by binding to the ABRE element of the MsDHN1 promoter. The transcriptional regulation of MsABF2 on MsDHN1 was dependent on the abscisic acid signaling pathway. These results indicate that MsDHN1 can increase alfalfa tolerance to Al stress via increasing oxalate secretion from root tips, which may involve in the interaction of MsDHN1 with two AQP.

The mitochondrial and chloroplast dual targeting of a multifunctional plant viral protein modulates chloroplast-to-nucleus communication, RNA silencing suppressor activity, encapsidation, pathogenesis and tissue tropism

Plant defense against melon necrotic spot virus (MNSV) is triggered by the viral auxiliary replicase p29 that is targeted to mitochondrial membranes causing morphological alterations, oxidative burst and necrosis. Here we show that MNSV coat protein (CP) was also targeted to mitochondria and mitochondrial-derived replication complexes [viral replication factories or complex (VRC)], in close association with p29, in addition to chloroplasts. CP import resulted in the cleavage of the R/arm domain previously implicated in genome binding during encapsidation and RNA silencing suppression (RSS). We also show that CP organelle import inhibition enhanced RSS activity, CP accumulation and VRC biogenesis but resulted in inhibition of systemic spreading, indicating that MNSV whole-plant infection requires CP organelle import. We hypothesize that to alleviate the p29 impact on host physiology, MNSV could moderate its replication and p29 accumulation by regulating CP RSS activity through organelle targeting and, consequently, eluding early-triggered antiviral response. Cellular and molecular events also suggested that S/P domains, which correspond to processed CP in chloroplast stroma or mitochondrion matrix, could mitigate host response inhibiting p29-induced necrosis. S/P deletion mainly resulted in a precarious balance between defense and counter-defense responses, generating either cytopathic alterations and MNSV cell-to-cell movement restriction or some degree of local movement. In addition, local necrosis and defense responses were dampened when RSS activity but not S/P organelle targeting was affected. Based on a robust biochemical and cellular analysis, we established that the mitochondrial and chloroplast dual targeting of MNSV CP profoundly impacts the viral infection cycle.

MULocDeep: A deep-learning framework for protein subcellular and suborganellar localization prediction with residue-level interpretation

Prediction of protein localization plays an important role in understanding protein function and mechanisms. In this paper, we propose a general deep learning-based localization prediction framework, MULocDeep, which can predict multiple localizations of a protein at both subcellular and suborganellar levels. We collected a dataset with 44 suborganellar localization annotations in 10 major subcellular compartments—the most comprehensive suborganelle localization dataset to date. We also experimentally generated an independent dataset of mitochondrial proteins in Arabidopsis thaliana cell cultures, Solanum tuberosum tubers, and Vicia faba roots and made this dataset publicly available. Evaluations using the above datasets show that overall, MULocDeep outperforms other major methods at both subcellular and suborganellar levels. Furthermore, MULocDeep assesses each amino acid’s contribution to localization, which provides insights into the mechanism of protein sorting and localization motifs. A web server can be accessed at http://mu-loc.org.

Genome-Wide Characterization of the MLO Gene Family in Cannabis sativa Reveals Two Genes as Strong Candidates for Powdery Mildew Susceptibility

Cannabis sativa is increasingly being grown around the world for medicinal, industrial, and recreational purposes. As in all cultivated plants, cannabis is exposed to a wide range of pathogens, including powdery mildew (PM). This fungal disease stresses cannabis plants and reduces flower bud quality, resulting in significant economic losses for licensed producers. The Mildew Locus O (MLO) gene family encodes plant-specific proteins distributed among conserved clades, of which clades IV and V are known to be involved in susceptibility to PM in monocots and dicots, respectively. In several studies, the inactivation of those genes resulted in durable resistance to the disease. In this study, we identified and characterized the MLO gene family members in five different cannabis genomes. Fifteen Cannabis sativa MLO (CsMLO) genes were manually curated in cannabis, with numbers varying between 14, 17, 19, 18, and 18 for CBDRx, Jamaican Lion female, Jamaican Lion male, Purple Kush, and Finola, respectively (when considering paralogs and incomplete genes). Further analysis of the CsMLO genes and their deduced protein sequences revealed that many characteristics of the gene family, such as the presence of seven transmembrane domains, the MLO functional domain, and particular amino acid positions, were present and well conserved. Phylogenetic analysis of the MLO protein sequences from all five cannabis genomes and other plant species indicated seven distinct clades (I through VII), as reported in other crops. Expression analysis revealed that the CsMLOs from clade V, CsMLO1 and CsMLO4, were significantly upregulated following Golovinomyces ambrosiae infection, providing preliminary evidence that they could be involved in PM susceptibility. Finally, the examination of variation within CsMLO1 and CsMLO4 in 32 cannabis cultivars revealed several amino acid changes, which could affect their function. Altogether, cannabis MLO genes were identified and characterized, among which candidates potentially involved in PM susceptibility were noted. The results of this study will lay the foundation for further investigations, such as the functional characterization of clade V MLOs as well as the potential impact of the amino acid changes reported. Those will be useful for breeding purposes in order to develop resistant cultivars.

Advances and perspectives in discovery and functional analysis of small secreted proteins in plants

Small secreted proteins (SSPs) are less than 250 amino acids in length and are actively transported out of cells through conventional protein secretion pathways or unconventional protein secretion pathways. In plants, SSPs have been found to play important roles in various processes, including plant growth and development, plant response to abiotic and biotic stresses, and beneficial plant-microbe interactions. Over the past 10 years, substantial progress has been made in the identification and functional characterization of SSPs in several plant species relevant to agriculture, bioenergy, and horticulture. Yet, there are potentially a lot of SSPs that have not been discovered in plant genomes, which is largely due to limitations of existing computational algorithms. Recent advances in genomics, transcriptomics, and proteomics research, as well as the development of new computational algorithms based on machine learning, provide unprecedented capabilities for genome-wide discovery of novel SSPs in plants. In this review, we summarize known SSPs and their functions in various plant species. Then we provide an update on the computational and experimental approaches that can be used to discover new SSPs. Finally, we discuss strategies for elucidating the biological functions of SSPs in plants.