Uniport

To provide comprehensive information of autophagy modulators for researchers, we searched not only for related proteins, but also related chemicals and microRNAs from peer-reviewed literatures, available databases and some websites. The detailed collection processes are described as follows.
Related proteins: Firstly, we searched and reviewed autophagy-related scientific articles recorded by PubMed as many as possible and extracted some useful information for us. In this step, we collected 545 autophagy-related genes from 499 literatures after removing duplicates. For these genes, their molecular type, specific effects on autophagy (e.g., their increased/decreased activity will increase/decrease autophagy), species evidence and corresponding experimental references were reserved. Additionally, their pathway and disease information have also been added including canonical pathways, downstream microRNAs, proteins and chemicals, upstream proteins and chemicals, role in cell, involved disease, OMIM information, KEGG disease information. After that, we searched for the autophagy-related database and found two excellent databases: Human Autophagy Database (HADb, http://www.autophagy.lu/) and the autophagy database (http://www.tanpaku.org/autophagy/, human). From them, we obtained 251 new related genes and their pathway information were collected from Autophagy Regulatory Network database. For all the collected genes, their corresponding uniport ID (Homo sapiens) and protein description were compiled manually. And then, 20 external database links containing structural and biological information were added: Gene ID, GI number, Uni Gene, PDB, disport, BioGrid, MINT, String, ChEMBL, DrugBank, Guide to Phar, Swisslipids, Biomuta, Ensembl protein, KEGG, Pharm GKB, Biocyc, Reactome, Unipathway, and Gene wiki.
Related chemicals: Similar to the protein collection process, we firstly collected 246 related chemicals from 367 literatures recorded by PubMed. For these chemicals, their molecular type, specific effects on autophagy (e.g., their increased/decreased activity will increase/decrease autophagy), species evidence and corresponding experimental references were reserved. Additionally, some pathway and disease information including target, pathway, biological description and corresponding gene name listed in aforementioned protein database. After that, we also obtained 595 new chemicals from MedChem Express, Selleck and APExBIO. Their research area, category (activator/inhibitor), in vitro/vivo test, clinical trials were reserved. For all the chemicals, some basic information was collected: IUPAC name, alternative names, canonical SMILES, molecular formula, molecular weight, solubility. Furthermore, 18 important physicochemical and ADME properties were calculated by our ADMETlab platform and chemopy package [22 (link)]: hydrogen acceptor, hydrogen donor, logD (pH = 7), pKa (pH = 7), pKb (pH = 7), druglike, logP(o/w), logS, SlogP, TPSA, loghERG, Caco-2, logBB, MDCK, logKp, logKhsa, human oral absorption, and percent human oral absorption (%). Four external links including structural and drug information were added: CAS number, PubChem CID, HMDB ID, and DrugBank ID.
Related microRNAs: In this part, we totally collected 132 autophagy related microRNAs from literatures recorded by PubMed and a noncoding RNA database, ncRDeathDB (www.rna-society.org/ncrdeathdb) after removing some duplicates [23 (link)]. Their molecular type, specific effects on autophagy (e.g., their increased/decreased activity will increase/decrease autophagy), species evidence and corresponding experimental references were reserved. Additionally, the gene description, RefSeq status, organism, synonyms and miRbase ID were also compiled to supply the biological information.

To construct the novel vaccine with low toxicity, allergenicity, and highly immunogenicity, we have analysed the different combination of sequence constructs. During this vaccine construction, firstly, sequence 62–106, 359–419 of B0VMD0 (uniport ID), and epitope sequence 688–787, 79–139, 366–382 of B0VUZ6 protein were joined with the help of amino acid linkers. Secondly, epitopes 162–204, 231–336 of B0VMD0 protein, and epitope 174–248, 636–659 of B0VUZ6 proteins were added with the help of linkers. For enhancing the immunogenicity of these two sequence constructs were added with the four different adjuvants L7/L12 ribosomal protein, beta-defensin, HBHA protein (M. tuberculosis, accession no. AGV15514.1), and HBHA conserved sequence^{53 (link)} respectively. PADRE peptide sequences were also incorporated along with the adjuvants. PADRE peptide induced CD4⁺ T-cells that improve efficacy and potency of peptide vaccine^{54 (link)}. Adjuvant HBHA and L7/L12 ribosomal protein are agonists to the TLR4/MD2 complex while beta-defensin adjuvant is agonist to TLR1, TLR2, and TLR4. The TLR’s interaction polarizes CTL responses which have a robust immuno-stimulatory effect^{53 (link)}. HEYGAEALERAG and GGGS linkers were conjugated with HTL, CTL and B epitopes, whereas adjuvants sequences were linked with the help of EAAAK linkers at both N- and C-terminus. Yang et al. proved that ‘GGGS linkers superior to ‘AAY’ as a ‘linkers’ of epitope-based vaccines^{55 (link)}. The fused vaccine constructs were used for further analysis.

Total RNA was extracted separately from testis (n = 4) and ovary (n = 4) tissues using TRIzol (Invitrogen). For each sample, RNA quality and concentration were assessed using agarose gel electrophoresis, a NanoPhotometer spectrophotometer (Implen, CA), a Qubit 2.0 Fluorometer (ThermoFisher Scientific), and an Agilent BioAnalyzer 2,100 system (Agilent Technologies, CA), requiring an RNA integrity number (RIN) of 8.5 or higher; one ovary sample failed to meet these quality standards and was excluded from downstream analyses. Sequencing libraries were generated using the NEBNext Ultra RNA Library Prep Kit for Illumina following the manufacturer’s protocol. After cluster generation of the index-coded samples, the library was sequenced on one lane of an Illumina Hiseq 4,000 platform (PE 150). Transcriptome sequences were filtered using Trimmomatic-0.39 with default parameters (Bolger et al., 2014 (link)). 30, 848, 170 to 39, 695, 323 reads were retained for each testis or ovary sample, and in total, 290, 925, 984 reads remained, with a total length of 42, 385, 060,050 bp. Remaining reads of all testis and ovary samples were combined and assembled using Trinity 2.12.0 (Haas et al., 2013 (link)), yielding 573,144 contigs (i.e., putative assembled transcripts). Contigs were clustered using CD-hit-est (95% identity). Completeness of this final de novo transcriptome assembly were assessed using the BUSCO pipeline (Simao et al., 2015 (link)).
Expression levels of contigs in each sample were measured with Salmon (Patro et al., 2017 (link)), and contigs with no raw counts were removed. To annotate the remaining contigs containing autonomous TEs, BLASTp and BLASTx were used against Repbase with an E-value cutoff of 1E-5 and 1E-10, respectively. The aligned length coverage was set to exceed 80% of the queried transcriptome contigs. To annotate contigs containing non-autonomous TEs, RepeatMasker was used with our Ranodon-derived genomic repeat library of non-autonomous TEs (LARD-, TRIM-, MITE-, and SINE-annotated contigs) and the requirement that the transcriptome/genomic contig overlap was >80 bp long, >80% identical in sequence, and covered >80% of the length of the genomic contig. Contigs annotated as conflicting autonomous and non-autonomous TEs were filtered out.
To identify contigs that contained endogenous R. sibiricus genes, the Trinotate annotation suite (Bryant et al., 2017 (link)) was used with an E-value cutoff of 1E-5 for both BLASTx and BLASTp against the Uniport database, and 1E-5 for HMMER against the Pfam database (Wheeler and Eddy, 2013 (link)). To identify contigs that contained both a TE and an endogenous gene (i.e., putative cases where a TE and a gene were co-transcribed on a single transcript), all contigs that were annotated both by Repbase and Trinotate were examined, and the ones annotated by Trinotate to contain a TE-encoded protein (i.e., the contigs where Repbase and Trinotate annotations were in agreement) were not further considered. The remaining contigs annotated by Trinotate to contain a non-TE gene (i.e., an endogenous Ranodon gene) and also annotated either by Repbase to include a TE-encoded protein or by blastn to include a non-autonomous TE were filtered out for the expression analysis.

According to the research on A. solani, we selected a relatively stable housekeeping gene "Actin" as the internal reference gene [27 (link), 28 (link)]. Specific primers for Actin and AsCEP50 were designed using the National Center for Biotechnology Information (NCBI) database (https://www.ncbi.nlm.nih.gov/). PP2A was selected as a housekeeping gene in N. benthamiana [29 (link)]. The SEN4, SAG12 and DHAR1 sequences were obtained from Uniport (https://www.uniprot.org/), and their specific primers were designed using Primer 3 Plus (https://www.primer3plus.com/). The cDNAs of the hyphae and growing on potato and N. benthamiana leaves were serial diluted to detect primer specificity. The RNAs were extracted using an Easy Pure Plant RNA Kit and cDNA were synthesized using a TransScript One-Step gDNA Removal and cDNA Synthesis SuperMix. The cDNAs were obtained using an Easy Pure Plant RNA Kit and a TransScript One-Step gDNA Removal and cDNA Synthesis SuperMix. All the primers used in qPCR were tested for amplification efficiency by serial dilution. The qRT-PCR was performed using the Bio-Rad CFX384 Touch Real-Time System (Bio-Rad), and the total reaction volumn was 20 μL containing 2 μL gene specific primers, 6 μL of cDNA and 10 μL of 2×Magic SYBR Mixture (CWBIO, Jiangsu, China). The qRT-PCR was performed under the following conditions: 95°C for 30 s, followed by 40 cycles at 95°C for 5 s and 59°C for 30 s. The threshold cycle (CT) values were used to determine the fold change in transcript accumulation with the 2^−ΔΔCt method [30 (link)]. Six biological and three technical replicates were performed for each sample in all the qRT-PCR reactions.