Caenorhabditis elegans membrane skeletal protein spectrin. We show that these mutations impair mechanical support for the plasma membrane and change cell shape. RNA sequencing (RNA-seq) analyses of spectrin-mutant animals uncovered a global down-regulation of ciliary gene expression, prompting us to investigate whether spectrin participates in ciliogenesis. Spectrin mutations affect intraflagellar transport (IFT), disrupt axonemal microtubules, and inhibit cilium formation, and the endogenous spectrin periodically distributes along cilia. Mammalian spectrin also localizes in cilia and regulates ciliogenesis. These results define a previously unrecognized yet conserved role of spectrin-based mechanical support for cilium biogenesis.Cilia are remarkable cellular devices that power cell motility and transduce extracellular signals. To assemble a cilium, a cylindrical array of 9 doublet microtubules push out an extension of the plasma membrane. Membrane tension regulates cilium formation; however, molecular pathways that link mechanical stimuli to ciliogenesis are unclear. Using genome editing, we introduced hereditary elliptocytosis (HE)- and spinocerebellar ataxia (SCA)-associated mutations into the  Introducing human disease-associated mutations in the membrane skeletal protein spectrin into the nematode Caenorhabditis elegans reveals that spectrin mutations down-regulate ciliary gene expression, affect intraflagellar transport, disrupt axonemal microtubule organization, and inhibit ciliogenesis. Cilia are evolutionarily conserved organelles that generate forces to drive cell motility and transduce chemical and physical signals to modulate cell behaviors –4. Many The spectrin-based membrane cytoskeleton maintains the structural integrity of the plasma membrane and protects cells from mechanical stresses . SpectriC. elegans genome only contains 1 α-spectrin (spc-1), 1 conventional β-spectrin (unc-70), and 1 heavy spectrin  gene ) and removed 9 amino acids in the SCA5-associated deletion in β-spectrin  and 88% of unc-70 (cas983) mutant animals survived and propagated (spc-1 (cas971) and 38% of unc-70 (cas983) progenies were paralyzed or showed uncoordinated movement -Cas9-based homologous recombination strategy, we succeeded in replacing L260P in α-spectrin  strains to label SPC-1 and UNC-70 with the green fluorescence protein (GFP) at the N or C terminus of spectrin . We next focused on the process of embryo elongation, during which actomyosin-based mechanic forces convert an embryo from a ball of cells into an elongated 3-fold vermiform shape. Nine out of 39 GFP::SPC-1L260P embryos but none of the GFP::SPC-1 embryos (N = 12) failed to complete embryonic elongation, and for the survived GFP::SPC-1L260P embryos, the length was markedly reduced  and 1,480 or 1,819 genes are down-regulated (fold change < −2 and p < 0.05) in spc-1 (cas971) or unc-70 (cas983) mutant animals, respectively  and B  subunits, IFT-dynein heavy (che-3), Bardet-Biedl syndrome proteins , transition zone (TZ) protein (mks-6), and ciliary membrane receptor (odr-10)—were down-regulated in both spectrin mutants  showed a high correlation between d unc-70 . We founectively  Tables. ectively . Using q mutants . These rspc-1 (cas971) or 10% unc-70 (cas983) mutant animals and that IFT was largely reduced in the residual cilia (spc-1 (cas971) or 10% unc-70 (cas983) animals failed to or reduced their capacity to uptake the fluorescent lipophilic dye DiI  through sensory cilia  KI marker, whose transcript level did not change in spectrin mutants. We found that the ciliary length was dramatically reduced from 7.5 μm to 2–3 μm in 13% al cilia . Consistry cilia , indicatry cilia .spc-1 (cas971) or unc-70 (cas983) mutant cilia. As shown in spc-1 (cas971) mutant animals and 6 out of 21 examined cilia from 2 unc-70 (cas983) worms showed defective axonemal structure: some of the spc-1 (cas971) or unc-70 (cas983) mutant cilia only contained 7 doublets in the middle segments, and some doublets were formed incompletely with an intact A tubule but an incomplete B tubule  or a small in-frame deletion in unc-70 (cas983). Considering that 38% of spc-1 (cas971) and 12% of unc-70 (cas983) mutant embryos did not survive to the larval stage for ciliary phenotype analysis  cells. Using anti-acetylated α-tubulin immunofluorescence as a cilium marker, we showed that α-spectrin localized in the cilia of IMCD3 cells . Furthercts Figs  and 4H. cts Figs  could beanalysis , the penanalysis .This work defined an important function of the spectrin-based membrane skeleton in ciliogenesis. Previous studies have discovered the core pieces of machinery that build and maintain cilia and chemical cues that instruct cilium assembly and disassembly –3, and ospc-1 or unc-70 mutant animals, we showed that the expression of spectrin from ciliated neurons but not from glial cells rescued ciliary defects  to select the target sequence. GFP and 7×GFP11 tag were added to the C terminus of SPC-1, whereas UNC-70 was tagged with an N-terminal GFP. We generated SPC-1-L268P and UNC-70-ΔH590-L598 mutation KIs (CRISPR-Cas9 targets were inserted to the pDD162 vector (Addgene #47549) by linearizing this vector with primers listed in e tag KI , homologtion KIs  in the STotal RNA was extracted from L1 worms with TRIzol  according to the manufacturer's protocol. The RNA quality was assessed on the Agilent Bioanalyzer 2100 system. The samples with RIN > 6 were processed; 50 ng to 500 ng of total RNA was used for library preparation using the KAPA RNA HyperPrep Kit . Library samples were sequenced on an Illumina HiSeq platform. A total of 150-bp paired-end reads were generated.C. elegans reference genome (ce10) using STAR (2.5.4b) and quantified by HTSeq (version 0.9.1). Only uniquely mapped reads were used to calculate the relative expression level of the gene. Differentially expressed genes (DEGs) were calculated using DESeq2 with adjusted p ≤ 0.05 and log2 fold change ≥ 1. Metascape was used to identify gene enrichment terms in up- or down-regulated genes. Raw sequencing reads were first trimmed using TrimGalore (version 0.4.4) to remove the low-quality bases and adaptor sequences. After trimming, paired-end reads with at least 20 nucleotides in length were aligned to cDNA was synthesized in a 20 μl reaction volume using the RevertAid First Strand cDNA Synthesis Kit ; 2 μl of 1:4 dilution of cDNA was used as the template in a 20 μl reaction volume from the FastStart Universal SYBR Green Master . A list of the real-time PCR primers is in the resource Young-adult worms were randomly collected into 200 μl M9 solution and mixed with equal volume dyes  at working concentration (20 μg/ml), followed by incubation at room temperature in the dark for 30 min. Worms were transferred to seeded NGM plates and examined for dye uptake 1 h later using a fluorescence stereoscope. At least 100 worms of each strain were examined in 2 independent assays.https://www.micro-manager.org) at an exposure time of 200 ms. Images of spectrin periodicity were collected on a Nikon  A1R laser-scanning confocal microscope with a CFI Plan Apo 100× oil immersion objective (NA 1.45) and 488-nm lasers with 150 nm X-Y resolution or a Hessian matrix-based structure illumination microscopy with 88 nm X-Y resolution.Young-adult worms were anesthetized with 0.1 mmol/L levamisole in M9 buffer and mounted on 3% agarose pads at 20°C. Live-cell imaging was performed on an Axio Observer Z1 microscope  equipped with a 100×, 1.49 numerical aperture (NA) objective, an electron-multiplying (EM) charge-coupled device (CCD) camera (Andor iXon+ DU-897D-C00-#BV-500), and the 488 nm and 561 nm lines of a Sapphire CW CDRH USB Laser System attached to a spinning disk confocal scan head (Yokogawa CSU-X1 Spinning Disk Unit). Our high-resolution live imaging system includes an Olympus IX83 microscope equipped with a 150×, 1.45 NA objective lens, a Neo 5.5 sCMOS Camera , and the same spinning disk confocal modules as mentioned above. Time-lapse images were acquired by μManager . After freezing, carriers were transferred into 2 ml microcentrifuge tube containing 1 ml acetone solution of 1% osmium tetroxide and 0.1% uranyl acetate  under liquid nitrogen. The tubes were then placed in Leica EM AFS2 machine and processed using standard FSF program: −90°C for 48 h, −60°C for 24 h, −30°C for 18 h, and finally to 4°C. Freeze-substituted fixed specimens were washed 3 times with pure acetone and infiltrated with SPI-PON 812 resin. The specimens were subsequently embedded in a flat mold and polymerized at 60°C; 90 nm sections were obtained with a Leica EM UC7 Ultramicrotome  and picked on 200 mesh copper grids. Sections were poststained with 2% uranyl acetate and Reynold’s lead citrate to enhance contrast and imaged on an FEI Tecnai G2 Spirit (120 kV) electron microscope .2 in air in DMEM/F12  containing 10% fetal bovine serum (FBS), 0.3 mg/ml glutamine , 100 U/ml penicillin , and 100 U/ml streptomycin . To induce ciliogenesis, cells were shifted from 10% serum to 0.05% serum for 24 h. Plasmids were transfected into cells using Lipofectamine 3000  following the manufacturer’s instructions. Cells were shifted from 10% serum to 0.05% serum for 48 h after transfection of shRNA to induce ciliogenesis before fixation. The target and control scrambled sequences were from the mouse shRNA library of Sigma. The control scrambled sequence was 5ʹ-CAACAAGATGAAGAGCACCAA-3ʹ. The alpha-spectrin Spta1 and Sptan1 shRNAs were a pool of 3 different plasmids, targeting the Spta1 sequence: 5ʹ-CCCACTAACATTCAGAGGAAA-3ʹ, 5ʹ-CCACCGTAACAGACGTGAAAT-3ʹ, 5ʹ-GCAGATCAAGAACTTTGAAAT-3ʹ, and targeting the Sptan1 sequence: 5ʹ-GCAGCAACAATTTAATCGAAA-3ʹ, 5ʹ-GCATCCACTAACAGAGGCAAA-3ʹ, 5ʹ-GCACACGAAGTACAGAGGTTT-3ʹ.IMCD3 cells were maintained at 37°C in 5% COCells for anti-acetylated tubulin staining were incubated on ice for 30 min before fixation to depolymerize cytoskeletal microtubules. Cells were fixed with 4% paraformaldehyde (PFA) for 15 min at room temperature. Cells were then washed 3 times with PBS and permeabilized in 0.5% Triton X-100 in PBS for 15 min. Cells were blocked in 4% bovine serum albumin (BSA) for 1 h at room temperature and incubated with primary antibodies at 4°C overnight. Primary antibodies used for immunofluorescence are mouse anti-acetylated-tubulin  and rabbit anti-SPTA1 . Alexa 488- or Alexa 549-conjugated secondary antibodies  were applied for 1 h at room temperature. DNA was stained with DAPI. Secondary antibodies used for immunofluorescence were Dylight 488, Goat Anti-Rabbit IgG ; Dylight 549, Goat Anti-Rabbit IgG ; Dylight 488, Goat Anti-Mouse IgG ; and Dylight 549, Goat Anti-Mouse IgG .t test analysis to determine the statistical differences as indicated in figure legends.ImageJ software was used to circumscribe the fluorescence field and to measure the fluorescence intensity. We used the two-tailed Student dyf-1::spc-1 and Pdyf-1::unc-70 constructs were generated using a PCR-fusion–based approach by placing a 454 bp ciliated neuron-specific promoter of dyf-1 adjacent to a DNA fragment containing spc-1 or unc-70 and its 3ʹ UTR amplified from the C. elegans genomic DNA. Pitr-1::spc-1 and Pitr-1::unc-70 constructs were generated using the same PCR-fusion–based approach by placing a 2,335 bp socket cell-specific promoter of itr-1 adjacent to a DNA fragment containing spc-1 or unc-70 and its 3ʹ UTR amplified from genomic DNA. Pvap-1::spc-1 and Pvap-1::unc-70 constructs were generated using a PCR-fusion–based approach by placing a 5,205 bp sheath cell-specific promoter of vap-1 adjacent to a DNA fragment containing spc-1 or unc-70 and its 3ʹ UTR amplified from genomic DNA. Transgenic lines carrying extrachromosomal arrays of the spc-1 or unc-70 expression constructs were generated by germline transformation with the selection marker Pegl-17::mCherry-Myri and Pegl-17::mCherry::TEV-S::his-24 into homozygous spc-1 (cas971) or unc-70 (cas983) mutant animals.PS1 DataData for (XLSX)Click here for additional data file.S1 Figspc-1 (L268P) (A) and unc-70 (ΔH590-L598) (B) mutations were confirmed by Sanger sequencing. The sequence of the engineered C. elegans genomic DNA containing the mutation is shown with the corresponding control sequence below. Arrows in the chromatogram indicate the site of the mutation. Red rectangles in the control sequence indicate the affected amino acids.Disease-associated (TIF)Click here for additional data file.S2 FigC. elegans development. The GFP KI embryos at the 1-cell stage, the 8-cell stage, comma stage, and the larva at L1 (upper right) or L4 (lower) stage were imaged. Scale bars, 5 μm in the upper panel and 50 μm in the lower panel. (C–D) The representative images of SPC-1 (C) and UNC-70 (D) from GFP KI animals. High magnification images of the selected regions in the yellow dotted boxes are shown in (A–B) The alpha-spectrin SPC-1 (A) and beta-spectrin UNC-70 (B) in (TIF)Click here for additional data file.S3 FigC. elegans (top). Scale bar, 1 μm. (C) Histogram of the spacings between adjacent of SPC-1::GFP (left) or GFP::UNC-70 (right) structures (N = 100–150 spacings), and the red line is a Gaussian fit. Data associated with this figure can be found in  A representative still image of SPC-1::GFP KI animal showing the distribution in neurites and membrane. (Right) Representative image of the seam cells from a double-labeled animal showing UNC-70  and SPC-1  co-localization (top). Scale bars, 5 μm. (B) Representative images of SPC-1::GFP (upper) or GFP::UNC-70 (lower) from the plasma membrane of seam cells in live (TIF)Click here for additional data file.S4 Fig(TIF)Click here for additional data file.S5 FigN = 117–273). Statistical significances between underlined pairs are based on Student t test, ***p < 0.001. Data associated with this figure can be found in Quantifications of the animals showing no staining (red) or weak staining (light red) defects in the dye-filling assay from WT, mutant animals, or their rescue animals ((TIF)Click here for additional data file.S6 FigYellow arrows indicate the boundary of socket cells. White asterisks indicate that vesicles accumulated in socket cells. TEM, transmission electron microscope.(TIF)Click here for additional data file.S7 FigC. elegans. sgRNAs targeting the 5ʹ or 3ʹ ends of genes and approximately 1 kb homology arms and fluorescent tags were inserted into HR templates. (B) Summary of CRISPR targets, homology arms, and tags. (C) Construction of HR templates to generate disease-related mutation KI strains. CRISPR targets and PAM motifs in WT genomes are colored in red and green, respectively. Disease-associated spc-1 (L268P) and unc-70 (ΔH590-L598) mutations in templates are colored in blue. CRISPR-Cas9, clustered regularly interspaced short palindromic repeats- Cas9; HR, homology recombination; KI, knock-in; PAM, protospacer adjacent motif; sgRNA, single-guide RNA; WT, wild type.(A) Schematic design of the CRISPR-Cas9–assisted KI for (TIF)Click here for additional data file.S1 MovieInverted fluorescence time-lapse movie of SPC-1::GFP embryo. Frames were taken every 2 min. The display rate is 7 frames per second. GFP, green fluorescence protein; KI, knock-in.(AVI)Click here for additional data file.S2 MovieInverted fluorescence time-lapse movie of SPC-1 (L268P)::GFP embryo. Frames were taken every 2 min. The display rate is 7 frames per second. GFP, green fluorescence protein; KI, knock-in.(AVI)Click here for additional data file.S3 MovieInverted fluorescence time-lapse movie of GFP KI GFP::UNC-70 embryo. Frames were taken every 2 min. The display rate is 7 frames per second. GFP, green fluorescence protein; KI, knock-in.(AVI)Click here for additional data file.S4 MovieInverted fluorescence time-lapse movie of GFP::UNC-70 (ΔH590-L598) embryo. Frames were taken every 2 min. The display rate is 7 frames per second. GFP, green fluorescence protein; KI, knock-in.(AVI)Click here for additional data file.S5 MovieImages were taken using a time-lapse fluorescence microscope attached to a spinning disk confocal scan head . Frames were taken at an interval of 200 ms. The display rate was 20 frames per second. Scale bar: 5 μm. GFP, green fluorescence protein; IFT, intraflagellar transport; WT, wild type.(AVI)Click here for additional data file.S1 TableCRISPR, clustered regularly interspaced short palindromic repeats.(DOCX)Click here for additional data file.S2 TableqPCR, quantitative polymerase chain reaction.(DOCX)Click here for additional data file.S3 Table(DOCX)Click here for additional data file.S4 TableSOE, splicing by overlapping extension.(DOCX)Click here for additional data file.S5 Table(DOCX)Click here for additional data file.S6 TableRNA-seq, RNA sequencing.(XLSX)Click here for additional data file.S7 TableRNA-seq, RNA sequencing.(XLSX)Click here for additional data file.


Trypanosoma brucei uncovered an essential protein (Tb927.10.7910) that is postulated to be an RNA-binding protein implicated in the regulation of the mitochondrial post-transcriptional gene regulatory network by its association with proteins that participate in a multi-protein RNA editing complex. However, the mechanism by which this protein interacts with its multiple target transcripts remained unknown. Using sensitive database searches and experimental data, we identify Z-DNA-binding domains in T. brucei in the N- and C-terminal regions of Tb927.10.7910. RNA-binding studies of the wild-type protein, now referred to as RBP7910 (RNA binding protein 7910), and site-directed mutagenesis of residues important for the Z-DNA binding domains show that it preferentially interacts with RNA molecules containing poly(U) and poly(AU)-rich sequences. The interaction of RBP7910 with these regions may be involved in regulation of RNA editing of mitochondrial transcripts.RNA-binding proteins play a particularly important role in regulating gene expression in trypanosomes. A map of the network of protein complexes in  Trypanosoma brucei, a unicellular kinetoplastid parasite, is its unique way of producing energy in different life cycle stages1. In the insect vector, the single mitochondrion in T. brucei undergoes extensive morphological alterations and changes in gene expression. One example of the regulation of mitochondrial gene expression is the insertion and deletion of uridine nucleotides during a unique post-transcriptional editing process that is restricted to kinetoplastids3.One of the most intriguing features of 5. Upon binding to the pre-mRNA, the gRNA 3′ (U)-tail interacts with the purine-rich region upstream of the editing site (ES). This interaction, which stabilizes the gRNA-pre-mRNA duplex, has been suggested to be a possible function of the gRNA 3′ (U)-tail7.Editing relies on mitochondrial-encoded small RNAs known as guide RNAs (gRNA) which contain the information needed for the proper addition of uridines to or deletion from pre-mRNAs to produce edited-mRNAs, which are translated into essential protein subunits of the respiratory chain. Additionally, gRNAs have (U)-tails at the 3′ end that are added post-transcriptionally by a mitochondrial terminal uridylyl transferase (TUTase)9, other dynamic multi-protein complexes have been identified. These include the RNA-editing mediator complex (REMC), guide RNA binding complex (GRBC), and the polyadenylation mediator complex (PAMC), collectively known as the RNA editing substrate-binding complex (RESC)12. The components of these complexes are essential for mitochondrial RNA editing and maturation of edited RNAs prior to translation. Some of the proteins in these complexes are needed for the processivity of the editing reaction and RNA utilization during this process14. Multiple proteins are transiently associated with the editosome or editing substrates to ensure accurate and efficient editing, and to influence the stability and abundance of mitochondrial RNAs. Some RNA-binding proteins (RBPs) bind mRNAs (pre-edited and edited transcripts) and/or gRNAs with various binding affinities16, or stabilize the gRNA conformation during the editing process16. For example, the paralogues GRBC1 and GRBC2 form a stable heterotetramer with a α2/β2 configuration in the core of MRB1 and help stabilize the gRNA17 by protecting the gRNA population from nucleolytic degradation18. gRNAs exhibit different primary sequences, but they share common secondary structures composed of two stem-loops and a 3′ oligo (U)-tail19.In addition to the editosome or RNA editing core complex (RECC), which catalyzes the enzymatic steps of the editing process21. On the other hand, other proteins show gRNA-binding ability mediated by the U-tail of the gRNA, such as KREPA4 in the RECC22, and the multifunctional RNA-binding protein RBP1623. The U-tail is likely a single-stranded molecule with a partially helical arrangement24 that helps stabilize the gRNA/mRNA duplex25. Pentatricopeptide repeat RBPs represent another group of RBPs in T. brucei, and include kinetoplastid polyadenylation factor 1, 2 (KPAF1/2)26, which functions in the synthesis of the long 3′ tail of edited mRNAs, and KPAF327, which is more crucial in the process of selecting pre-mRNAs for adenylation rather than uridylation before entering the editing pathway.The gRNA-binding proteins MRP1/2 bind gRNA via non-sequence-specific electrostatic interactions28. Down-regulation of this protein indicated its essential role in cell viability via editing of the apocytochrome b mRNA in the insect form of T. brucei. Another study also showed RNA-dependent interactions of the protein in tandem affinity purification of multiple subunits of the RESC12. Recently, Tb927.10.7910 was described as lacking specific motifs and to be part of a complex named the PPsome29. This study illustrated the link between the PPsome and the RESC and its role in converting the mitochondrial transcription-defined 5′ terminus into a monophosphorylated state.We previously reported a mitochondrial protein (Tb927.10.7910) that interacts with REMC5A and TbRGG2, subunits in the RESC, in an RNA-dependent manner31. In vitro RNA-binding and competition assays revealed the RNA-binding activity of the recombinant protein , which recognizes multiple mitochondrial RNA classes containing poly(U) and poly(AU)-rich sequences through the nucleic acid recognition core of its Z-DNA-binding domains.In the present study, we identified two winged helix-turn-helix (HTH) structured Z-DNA- binding domains in Tb927.10.7910, resembling a conserved family of proteins with Z-DNA-binding domains (ZBPs), known to bind specifically to Z-DNA and/or Z-RNA32 and PSI-BLAST33 were used to interrogate potential biological functions of RBP7910 based on homologous proteins identified in a sequence search. The similarity search tools based only on sequence returned no relationships to proteins with known function. In an alternative strategy, we used HHpred, a highly sensitive method for searching for more remotely homologous relationships34. Using an improved version of profile-sequence comparison, Profile Hidden Markov Models (HMMs), HHpred predicted two potential Z-DNA-binding domains in the N- and C-terminal regions of RBP7910. The N- or C-terminal sequences were input into HHpred or I-TASSER server instead of the complete sequence36 and dramatically improved the accuracy of the predicted function and secondary structure of each domain. The secondary structure prediction showed three-helix bundles and three β-sheets with an αβααββ topology for both domains. Similar α/β HTH architecture, consisting of three α-helices and three β-strands, has been observed in Z-DNA-binding proteins (ZBPs)38. Multiple sequence alignment of N- and C- terminal domains of RBP7910 with some of its orthologs and corresponding domains of known ZBPs is shown in Fig. 41. ADAR1, DLM-1, and PKZ contain two Z-DNA-binding domains , whereas E3L has one Zα domain. The nucleic acid binding activity of the Zα and Zβ domains of different ZBPs has been widely studied. The Zα domain exhibits a higher level of sequence conservation than the Zβ domain. Crystallographic data for ZBPs showed that residues from α3 and the β2/β3 wing region serve as the nucleic acid binding interfaces42 , CYb gRNA (gCYb [558] USD-2A-42nt)44, native CYb gRNA (gCYb [558])45, CYb pre-mRNA46, and CYb edited-mRNA47 were in vitro transcribed and labeled with [α- 32P] either during transcription or after transcription at the 3′ end of the mRNA. Despite the detection of a protein-RNA complex between recombinant RBP7910 and gA6[14] and pre-and edited CYb mRNAs, we did not detect binding between this protein and the A6 pre-mRNA or any CYb gRNA variant (data not shown).We determined the binding affinity of recombinant RBP7910 for radiolabeled gRNAs and pre-edited and edited mRNAs using electrophoretic mobility shift assay (EMSA) to assess the RNA-binding ability of predicted Z-DNA-binding domains of RBP7910. RNA substrates including (gA6[14])The incubation of a fixed amount of RBP7910 with increasing concentrations of radiolabeled gA6[14] or pre-edited and edited CYb mRNAs resulted in the formation of a slowly migrating protein-RNA complex Fig. . The Kd To support these results, we performed competition experiments using labeled gA6[14] RNA, unlabeled CYb gRNA variants and CYb mRNAs as competitors. The natural gCYb RNA with the U-tail competed for binding between RBP7910 and gA6[14] RNA 10 times better than the 42-mer CYb gRNA without the U-tail Fig. . The samGel shift assays were conducted to examine the specificity of binding of each substrate using radiolabeled substrates in the presence of increasing concentrations of unlabeled RNAs, including gA6[14] and pre- and edited CYb mRNAs. Unlabeled homologous RNAs reduced binding at the same molar ratios of labeled RNAs and eliminated RBP7910-labeled RNA interactions at 10-fold molar excess concentrations -tail of the gRNA by performing a competition assay using unlabeled gA6[14] RNA lacking the U-tail with gA6[14] RNA Fig. . While aThus, we used a uridylated non-guide RNA (49 nt) as the competitor to more comprehensively investigate the contributions of stem-loop elements (secondary structure) and the U-tail in the RBP7910-gRNA interaction Fig. . This RN11. We compared the total gRNA population between Tet-induced and uninduced cells expressing a RBP7910 knock-down RNAi construct 3 and 4 days post-induction28 using guanylyl transferase labeling to determine the contribution of RBP7910 to the stability of the total gRNA population  or the poly AU-tail of mitochondrial transcripts. Although we have shown binding of RBP7910 to the AU sequence, we could not determine if this interaction is purely sequence specific or mediated by the secondary structures of the sequence. Considering the binding preference of RBP7910 for the poly AU sequence, we propose that this protein is likely to be involved in RNA editing or translation of mRNAs containing an AU-tail.52. This domain specifically recognizes the Z-form of DNA/RNA molecules in a conformation-specific manner. Because RBP7910 and ZBPs exhibit a similar fold, we examined whether they also shared the same nucleotide-binding interface. Zα and Zβ are structurally homologous domains with a similar arrangement of α helices and β sheets (αβααββ), with the exception of the presence of one extra helix (α4) in ZβADAR1, which is mostly involved in dimerization of the protein37.Following experimental establishment of the RNA-binding activity of RBP7910, we were interested in identifying residues that affect RNA binding based on sequence and structural alignments. Structural predictions and sequence analysis of RBP7910 identified two putative Z-DNA-binding domains in the N- and C-termini of RBP7910. The Z-DNA-binding domain family belongs to the superclass of protein with WHTH domains, and this superclass is largely present in the DNA-binding domain of prokaryotic transcription factors and some eukaryotic transcription factors53. As shown in Fig. 54. These residues are also conserved in the hZβDLM-1/Z-DNA complex53, although with a different hydrogen bonding pattern. Furthermore, ZBPs contain one or two proline (P192-P193 of hzαADAR1) residues that contribute to the Zα DNA-binding activity via hydrophobic interactions. These proline residues are usually located adjacent to a polar residue such as Thr or Asn, which interacts with DNA through water-mediated hydrogen bonds55. No equivalent residue for the Pro or Thr residues of Zα are present in Zβ domains.The RNA-binding function of RBP7910 was probed by replacing candidate RNA-contact residues in the N- and C- terminal domains of RBP7910 with alanine. Sequence comparisons of different ZBPs suggested the presence of a common nucleic acid recognition core containing hydrophobic and positively charged amino acids in the α3 core and the β2/β3 wing56 or the corresponding residues in mZαDLM-1 and mZβDLM-157 eliminated the DNA-binding ability of each domain without altering protein stability.A few mutagenesis studies have investigated the Z-DNA/RNA-binding activities of ZBPs. For instance, alanine substitution for Asn173 and Tyr 77 in hZαADAR1Trypanosoma genera and Trp56 is conserved in kinetoplastids. Arg53 is also shared among Trypanosoma genera, Pro76 in Trypanosoma genera and C. fasciculata, and Pro77 and Trp79 are conserved in kinetoplastids. Different amino acids from the N- and C-terminal domains of RBP7910 were selected for mutagenesis studies based on (1) conservation of amino acids located in the recognition core of ZBPs, (2) previously reported point mutations affecting nucleic acid-binding activity of ZBPs, and (3) avoiding residues previously reported to be crucial for the protein stability.The N-terminal domain of RBP7910 showed a high level of conservation for residues in the nucleic acid recognition core of ZαZBPs  of RBP7910 were Thr52, Arg53, and Trp56; Pro76, Pro77, Trp79 were selected from the β2/β3 wing. Because of the lower conservation of the Zβ domain of ZBPs and kinetoplastids, only Pro164, Phe167, and Trp188 from the Zβ recognition core were chosen for mutagenesis analysis of the second predicted Z-DNA-binding domain of RBP7910.A gel retardation assay was employed to assess the effects of each point mutation on the binding of 54. Previous mutagenesis studies showed a negative effect of P192A on DNA-binding activity of hZαADAR1, while the P67A substitution, with a Kd value of 0.18 ± 0.01 nM; 95% CI:0.13,0.31, showed 1.2-fold better binding affinity than WT RBP7910 ) hydrolase, which with MERS2 PPR RNA-binding factor constitutes a 5′ pyrophosphohydrolase complex termed the PPsome. Therefore, we provide new insights into the role of RBP7910 in 5′processing of pre-edited transcripts as part of the PPsome. Identification of the PPsome purine-rich sites in 5′pre-edited transcripts with three Us at their 3′ end as the binding site of MERS2 along with the poly U binding affinity of RBP7910 suggests a role for RBP7910 in mitochondrial editing by engaging an RNA-dependent interaction of the PPsome with the RESC.The data presented here identify the first Z-DNA-binding domain in a 60. Based on the results of the RBP7910 binding assays, in addition to the 3′oligo (U)-tail, the secondary structure of gRNAs is also important for the gRNA-binding activity of RBP7910. The secondary structure conformation of purine-pyrimidine repeats in DNA/RNA strands is the main factor responsible for the recognition of these molecules by ZBPs59. By considering the importance of the secondary structure for gRNA-binding by RBP7910 and the AU sequence binding preference of this protein, we suggest a crucial role for the secondary structure of the purine-pyrimidine AU-rich sequences for RBP7910 RNA-binding.The high affinity of RBP7910 for U-rich and AU-rich RNA is consistent with Z-like steps found in RNA as r(U/ApA) dinucleotide repeats at key locations in single-stranded RNA regions and riboswitches54, suggesting that Zα binds to Z-DNA/RNA substrates using similar binding interfaces61. Compared to other ZBPs, the residues involved in nucleic acid recognition by RBP7910 are conserved but not identical, with few exceptions. However, alanine substitution point mutations of residues in the predicted binding interfaces only resulted in ~2–4 fold reduction in affinity of RBP7910 for RNA, lower than reported in other mutational studies of ZBPs61. One example of the Kd estimation is the Y177A substitution in ZαADAR1, which resulted in a 17.5-fold decrease in binding of a Z-DNA substrate compared to the WT protein40. It should be noted, however, that previous mutational analyses were performed based on the interaction of ZαADAR1 with DNA. We speculate that the discrepancy between the mutational effects is due to higher stability of the RNA-protein interaction. The ribose 2′-OH groups of RNA can make either direct or water-mediated hydrogen bonds with amino acids at the binding interfaces, and therefore single point mutations would not have a significant effect on RNA binding62.The interaction of Zα with the sugar-phosphate backbone of left-handed Z-DNA/RNA has been widely investigatedT. brucei.In summary, mutational studies support the RNA-binding function of the recognition core in the Z-DNA-binding domains of RBP7910. Further experiments, such as the construction of RBP7910 Zα and Zβ truncations, will facilitate studies of the contribution of each domain to the RNA-binding activity of the protein. The nucleic acid binding activities of winged HTH domain-containing proteins have different biological implications in cells, such as the regulation of transcription, RNA biogenesis, translation, and immune responses. Similarly, the elucidation of the mode of RNA-binding activity in RBP7910 will be an interesting topic for future research to characterize possible regulatory roles of RBP7910 in mitochondrial RNA processing in 63, resulting in the prediction of two Z-DNA-binding domains in the N- and C-terminal regions of Tb927.10.7910. The amino acid sequence of the N-terminal region of Tb927.10.7910, its orthologues in multiple kinetoplastid species (www.tritrypdb.org), and the Z-alpha (Zα) domain of ZαADAR1, DAI or ZBP1/ZαDLM-1, virus E3L (ZαE3L), and protein kinase containing a Z-DNA-binding domain (ZαPKZ) were aligned using Clustal Omega65. The same alignment was performed for the C-terminal region of Tb927.10.7910, the orthologues, and Z-beta (Zβ) of ZβADAR1, ZβDLM-1, and ZβPKZ domains.The RBP7910 sequence was analyzed for the presence of recognizable domains using HHpred66 was cloned into the pET30-a vector between NdeI and XhoI restriction sites to generate an N-terminal 6x His-tagged protein. The pET30-a/Tb927.10.7910 construct was used as the template to create nine individual alanine substitution point mutations. The point mutations located in the N-terminus of the protein included Thr52A, Arg53A, and Trp56A in the α3 region, Pro76A, Pro77A, and Trp79A in the wing region (β2-strand-loop-β3-strand) and Pro164A, Phe167A, and Trp188A in the C-terminal domain. All mutants were prepared by GenScript Corporation .The ORF of Tb927.10.7910 lacking the N-terminal mitochondrial import signal lysy/Iq competent E. coli strain (New England Biolabs SITE), which was grown to a density of 0.6 OD before induction with 0.5 mM isopropyl β-D-1-thiogalactopyranoside (IPTG). Bacterial cultures were grown after induction for either 5 h at 30 °C or 8 h at 16 °C, and then collected by centrifugation at 8,000 x g for 15 min at 4 °C. The cell pellet from 1 L of induced culture was resuspended in 50 ml cold PBS (pH 7.2), 10% glycerol, and 1X protease inhibitor mixture (Roche Applied Science), and cells were lysed by sonication on ice for 5 min, followed by centrifugation at 16,000 x g for 15 min at 4 °C. The cleared lysate was applied to a column with 2 mL IMAC Nickel charged resin (Bio-Rad). Proteins were eluted with an increasing gradient of imidazole from 10 mM to 320 mM, prepared in cold PBS containing 10% glycerol. Eluted fractions were dialyzed against two changes of buffer (PBS with 10% glycerol). The dialyzed recombinant proteins were applied to an Amicon centrifugal filter device (Millipore) and concentrated to 1/5 of the starting volume.The pET30-a expression vector was transformed into the T7 Express The relative sizes of the recombinant proteins were examined using SDS-PAGE Fig.  using an6, which specifies the first ES of the ATPase subunit 6 (A6) pre-mRNA. A Riboprobe System-T7-promega kit was used for in vitro transcription of 2 μg template DNA22. The CYb pre-mRNA (102 nt)67 and edited CYb mRNA were transcribed from BamHI linearized plasmid and synthetic DNA antisense template with a T7 promoter sequence, respectively, using a RiboMAX Express-T7-promega kit. Transcripts were either labeled with [α- 32P] UTP (Perkin Elmer) during transcription or were radiolabeled after transcription with [α- 32P] pCp at the 3′ end using T4 RNA ligase (New England Biolabs).Purified PCR fragments of gA6[14] Δ16G were amplified from the previously described plasmid encoding gA6[14] Δ16Gin vitro transcription of the NotI linearized plasmid. The pre-edited A6U5 transcript template was PCR amplified from the plasmid containing its sequence and used in the in vitro transcription reaction containing the A6U5 pre-mRNA. All RNAs were purified on 9% polyacrylamide/7 M urea gels.Unlabeled RNAs used in competition assays were synthesized from the DNA oligonucleotides listed in Table 68. For estimating Kd, increasing concentrations of purified RBP7910 (wild-type and point mutations) proteins were incubated with fixed concentrations of the labeled RNA (gA6[14] substrate and pre- and edited CYb mRNAs). For the gel shift assays, labeled RNAs were heated at 75 °C for 3 min followed by a slow cooling period with a rate of 1 °C/min to 23 °C, and held for 30 min at 23 °C before transferring the RNAs to the ice. Binding reactions were conducted in RBB50 buffer , 100 mM KCl, and 20 units RNasin (Promega) in a 20 μl volume for 30 min at RT. Samples were mixed with gel loading dye  before loading onto native 10% TBE gels that were pre-run at 110 V for 15 min in 0.5 X TBE at 4 °C. After 2 h, gels were fixed with 10% isopropanol plus 7% acetic acid for 30 min and visualized using a PhosphorImager (Bio-Rad). Free and bound RNAs were quantified using Quantity One software (Bio-Rad). The sum of the bound complexes in each lane was considered the total bound fraction. Data were analyzed with nonlinear curve fitting methods using GraphPad Prism 7 software . The values of Kd app and active protein concentrations, Bmax, were determined as best fits to the experimental data. The obtained Kd app values were used to calculate the active protein concentration and the corrected equilibrium dissociation constant using increasing concentrations of labeled RNAs relative to a fixed concentration of protein (wild-type and point mutants). The protein concentration was equivalent to approximately two times the estimated Kd app values.The apparent equilibrium dissociation constant (Kd app) was calculated for each RNA substrate by performing EMSAsCompetition experiments were performed as described above using a fixed amount of protein that resulted in approximately 30–50% bound RNA. A saturating concentration of the radiolabeled gA6[14], CYb pre-mRNA, edited CYb mRNA, and AU target substrate was used in separate binding reactions and mixed with 1-, 10-, 100-, and 1000-fold molar excess concentrations of unlabeled competitor RNA in the RBB50 binding buffer prior to addition of the protein. Percent competition was estimated as the ratio of bound RNA in the presence of unlabeled competitor relative to RNA bound in the absence of competitor.32P] of GTP (3000 Ci/mmol) using a ScriptCap™ m7G Capping System kit (CELLSCRIPT™), according to the manufacturer’s instructions. Reactions were extracted with phenol: chloroform twice and chloroform once and precipitated. Samples were mixed with 80% formamide loading buffer and resolved on 8% acrylamide-7 M urea gel in 1 X TBE.RNA was isolated from (−Tet) and (+Tet) PF Tb927.10.7910 RNAi cells 3 and 4 days after Tet induction, and treated with DNase as described above. Eight micrograms of DNase-treated RNA were labeled with 10 μCi [α-


The nucleotides of RNA appear to be products of evolution. Experimental studies are showing that plausible proto-nucleotides can be formed in simulated early Earth environments. In turn, these results help to clarify the prebiotic processes that give rise to nucleotides. The origin of the first nucleotides and the origin of RNA are related open questions, but they are not the same. That is, there may have been different nucleotides, and many more of them, on the prebiotic Earth than are found in extant RNA. The prebiotic synthesis of the RNA nucleotides is a tall order, and so is the prebiotic formation of RNA polymers (even with pre-formed nucleotides). Uncovering the origins of nucleotides and genetic polymers requires understanding the various chemical reactions that produce such molecules, whether or not (or how much) RNA nucleotides have evolved from earlier forms, and what prebiotic environments facilitate their formation.1. In the RNA-later camp, the extant RNA nucleotides are considered to be products of chemical and/or early biological evolution2. Both camps face substantial challenges in reconstructing the actual historical origin of nucleotides, but the challenges are quite different. The RNA-first proponents have an advantage in that they know exactly which molecules they seek to produce with model prebiotic reactions. However, they are limited by the chemical stability, reactivity, and functionality of the molecular subunits that comprise the extant nucleotides. Consequently, the RNA-first proponents must, understandably, sometimes rely on specific minerals  or geological events  to control, guide, or initiate a particular reaction or reaction sequence4. The RNA-later proponents, on the other hand, can draw from a wider variety of molecular building blocks, including molecules with more favorable properties for spontaneous nucleotide formation. However, with this increased freedom comes the liability of becoming lost in the vast chemical space of possible prebiotic molecules without ever finding the nucleotides that initiated the evolutionary march toward RNA.In the search for the origins of nucleotides and RNA, there are two main camps, or schools of thought. In the RNA-first camp, RNA arose abiotically and is the first informational polymer of life, with its nucleotides and polymers produced entirely by geochemical reactions5. That is, both the bond connecting phosphate to ribose and the bond between ribose and the nucleobase release a water molecule as they are formed  would have concentrated dissolved nucleotide subunits during a dry season and perhaps even during the daylight hours of a diurnal cycle. Heating the dry surface would also promote nucleotide formation by providing the kinetic energy needed for condensation of co-deposited nucleotide subunits. This drying pond model for prebiotic nucleotide synthesis is simple, thermodynamically sound, and easy to imagine on the early Earth. Nevertheless, attempts to produce the extant nucleotides in laboratory models of such environments, by drying and heating mixtures of nucleotide subunits, have failed to produce nucleotides in meaningful amounts. In particular, drying and heating adenine, cytosine, guanine, and uracil with ribose does not result in bond formation between ribose and these nucleobases, or only in very low yields2. We hypothesize that the early nucleotide subunits reacted more easily with each other to form proto-nucleotides when dried and heated on the surface of the early Earth. Our experimental investigations of this hybrid drying-pond/RNA-later hypothesis have resulted in the identification of nitrogen-containing heterocycles (molecules similar in structure to the nucleobases of RNA) that spontaneously form nucleotide-like molecules in good yields when dried and heated with ribose or with other sugars7.My co-workers and I find the drying pond model to be the most plausible scenario for the prebiotic synthesis of nucleotides. We are also are proponents of the RNA-later scenario. We have hypothesized that ribose and the four nucleobases have evolved from related molecular subunits that constituted the earliest nucleotides Fig. 2. We hyp8, apparently because wet phases enable redistribution of unreacted molecules to more favorable locations/orientations for nucleotide formation during the next dry phase. Additionally, biological polymers function only in the hydrated state, so at some point water must be added to polymers of RNA (or proto-RNA) nucleotides. It is therefore likely that evolutionary pressures at the polymer level in the solution state, such as duplex stability and the ability to form catalytic structures9, set the prebiotic nucleotides on a path of incremental changes that eventually produced the extant nucleotides.We also believe that the wet phases of wet–dry cycles played an important role in the synthesis and early evolution of nucleotides. It is unlikely that the subunits of the prebiotic nucleotides would have been formed and initially deposited in the same locations. In which case, hydration cycles would have been critical for mobilizing and bringing the subunits together. On a microscopic scale, model prebiotic nucleotide yields can increase when dried subunit mixtures are regularly rehydrated5). However, we now are able to conduct most nucleotide synthesis experiments between 55° and 85 °C. Our recent discovery of more reactive model proto-nucleobases permits this less extreme temperature range. This reduction in temperature is important because the prebiotic building blocks  show rapid increases in degradation rates above 85 °C. Some model prebiotic reactions we study do not occur at temperatures below 55 °C. Significantly, temperatures between 55° and 85 °C were likely common on Earth’s surface at the time when life began10.Results from our model laboratory experiments on prebiotic nucleotide synthesis are used to optimize future experiments and to provide a refined understanding of the environments on the early Earth that gave rise to nucleotides. For example, we first studied the reactions of ribose with alternative nucleobases at 100 °C because this high temperature was required to see any evidence of bond formation between ribose and adenine  are formed when a concentrated solution of urea is placed in a sealed reaction vessel under a model prebiotic atmosphere12, urea has a solubility of around 8 M in water (making it freely mobile in precipitation and runoff), and urea is a very stable molecule, which allows for its accumulation. Urea also forms water-free and low-water eutectic liquids with a number of organic compounds and inorganic salts. This property increases the availability of urea and other potentially important ingredients for nucleotide synthesis. For example, we have found that some urea-based liquids liberate phosphate from hydroxyapatite, a mineral that is essentially insoluble in water and whose lack of solubility had been viewed as an obstacle to phosphate incorporation into nucleotides of the early Earth13.Although not obvious at first, we think that large regions of concentrated urea were common on the surface of the prebiotic Earth that were similar to today’s Bonneville Salt Flats of Utah. These urea flats are possible because urea is a major product of model prebiotic atmospheric reactionsCurrently, based on the findings presented above, we conclude that the most favored environment for prebiotic nucleotide formation on the early Earth was a pond on dry land, with dissolved nucleotide subunits, and a substantial concentration of urea Fig. . This poOur search for the origin of nucleotides has shown that the drying pond model naturally enables the prebiotic formation of nucleotides if we accept that the first nucleotides were different from extant nucleotides. Further experimental investigations will bring us continuously closer to identifying the earliest nucleotides that initiated the evolutionary march toward RNA. I am optimistic that such lost treasures of the pre-RNA World will be revealed in the future if we do not, as a research community, prematurely declare the origin of nucleotides and nucleic acids a solved problem.


Equine adipose-derived mesenchymal stromal cells (e-AdMSC) exhibit attractive proregenerative properties strongly related to the delivery of extracellular vesicles (EVs) that enclose different kinds of molecules including RNAs. In this study, we investigated small RNA content of EVs produced by e-AdMSC with the aim of speculating on their possible biological role.  EVs were obtained by ultracentrifugation of the conditioned medium of e-AdMSC of 4 subjects. Transmission electron microscopy and scanning electron microscopy were performed to assess their size and nanostructure. RNA was isolated, enriched for small RNAs (<200 nt), and sequenced by Illumina technology. After bioinformatic analysis with state-of-the-art pipelines for short sequences, mapped reads were used to describe EV RNA cargo, reporting classes, and abundances. Enrichment analyses were performed to infer involved pathways and functional categories.  Electron microscopy showed the presence of vesicles ranging in size from 30 to 300 nm and expressing typical markers. RNA analysis revealed that ribosomal RNA was the most abundant fraction, followed by small nucleolar RNAs . Miscellaneous RNA (misc_RNA) reached 4.57% of the total where Y RNA, RNaseP, and vault RNA represented the main categories. miRNAs were sequenced at a lower level (3.51%) as well as protein-coding genes (1.33%). Pathway analyses on the protein-coding fraction revealed a significant enrichment for the “ribosome” pathway followed by “oxidative phosphorylation.” Gene Ontology analysis showed enrichment for terms like “extracellular exosome,” “organelle envelope,” “RNA binding,” and “small molecule metabolic process.” The miRNA target pathway analysis revealed the presence of “signaling pathways regulating pluripotency of stem cells” coherent with the source of the samples.  We herein demonstrated that e-AdMSC release EVs enclosing different subsets of small RNAs that potentially regulate a number of biological processes. These findings shed light on the role of EVs in the context of MSC biology. GO analysis revealed enrichment for terms related to extracellular content such as “extracellular exosome” or outer membranes with the cellular component (CC) vocabulary. “RNA binding” and “oxidoreductase activity” are among the most represented ones for molecular function whereas “cellular protein metabolic process” and “translation” for biological process vocabulary (see Additional The analysis of the protein-coding gene cargo revealed a clear enrichment signature. Network analysis showed that there was a significant enrichment for the “ribosome” pathway with 53 proteins out of the 154 considered  and 13 pSeveral papers speculated about the possible presence of distinct RNA species in a different subpopulation of EVs. Besides microvesicles produced by cell shedding,  they demFinally, it should be emphasized that the great individual variability between the samples is consistent with previous literature findings observed in different species where a similar degree of divergence between samples has been found. Further studies and a larger sample would be useful to better dissect this issue.MSC-derived EVs retain per se a huge therapeutic potential through beneficial properties related to the activation of protein synthesis, cell proliferation, and angiogenesis. The small RNA cargo, characterized for the first time in the equine species via deep sequencing, seems to specifically diffuse this message through a plethora of regulating RNA species and genes that belong to meaningful pathways.The elucidation of the mechanisms underlying their biological effects needs to be deeply explored in view of a future clinical use.


What is the agreement between prospective and retrospective measures of childhood maltreatment?This systematic review and meta-analysis of 16 unique studies and 25 471 unique participants found poor agreement between prospective and retrospective measures of childhood maltreatment, with Cohen κ = 0.19. On average, 52% of individuals with prospective observations of childhood maltreatment did not retrospectively report it, and likewise, 56% of individuals retrospectively reporting childhood maltreatment did not have concordant prospective observations.Because findings from this meta-analysis demonstrated that prospective and retrospective measures of childhood maltreatment identify largely different groups of individuals, the 2 measures cannot be used interchangeably to study the associated health outcomes and risk mechanisms. This systematic review and meta-analysis assesses the agreement between prospective and retrospective measures of childhood maltreatment. Childhood maltreatment is associated with mental illness. Researchers, clinicians, and public health professionals use prospective or retrospective measures interchangeably to assess childhood maltreatment, assuming that the 2 measures identify the same individuals. However, this assumption has not been comprehensively tested.To meta-analyze the agreement between prospective and retrospective measures of childhood maltreatment.child* maltreatment, child* abuse, child* neglect, child bull*, child* trauma, child* advers*, and early life stress combined with prospective* and cohort.MEDLINE, PsycINFO, Embase, and Sociological Abstracts were searched for peer-reviewed, English-language articles from inception through January 1, 2018. Search terms included Studies with prospective measures of childhood maltreatment were first selected. Among the selected studies, those with corresponding retrospective measures of maltreatment were identified. Of 450 studies with prospective measures of childhood maltreatment, 16 had paired retrospective data to compute the Cohen κ coefficient.Multiple investigators independently extracted data according to PRISMA and MOOSE guidelines. Random-effects meta-analyses were used to pool the results and test predictors of heterogeneity.The primary outcome was the agreement between prospective and retrospective measures of childhood maltreatment, expressed as a κ coefficient. Moderators of agreement were selected a priori and included the measure used for prospective or retrospective assessment of childhood maltreatment, age at retrospective report, sample size, sex distribution, and study quality. P < .001). Agreement was higher when retrospective measures of childhood maltreatment were based on interviews rather than questionnaires  and in studies with smaller samples . Agreement was not affected by the type of prospective measure used, age at retrospective report, sex distribution of the sample, or study quality.Sixteen unique studies including 25 471 unique participants  contained data on the agreement between prospective and retrospective measures of childhood maltreatment. The agreement between prospective and retrospective measures of childhood maltreatment was poor, with κ = 0.19 (95% CI, 0.14-0.24;Prospective and retrospective measures of childhood maltreatment identify different groups of individuals. Therefore, children identified prospectively as having experienced maltreatment may have different risk pathways to mental illness than adults retrospectively reporting childhood maltreatment. Researchers, clinicians, and public health care professionals should recognize these critical measurement differences when conducting research into childhood maltreatment and developing interventions. Researchers use retrospective reports as a shortcut to better understand the consequences of childhood maltreatment without the significant time or financial investment needed to undertake cohort studies.2 Clinicians use retrospective reports to swiftly identify individuals who are at heightened risk of mental illness by virtue of their exposure to childhood maltreatment.3 Public health professionals use retrospective reports to pragmatically estimate the health burden associated with exposure to childhood maltreatment.4 All these practices rely on the assumption that retrospective reports and prospective measures identify the same, or at least similar, groups of individuals. However, qualitative reviews6 have raised concerns about the validity of this assumption. Herein we present, to our knowledge, the first quantitative assessment of the agreement between retrospective reports and prospective measures of childhood maltreatment.Do prospective and retrospective measures of childhood maltreatment identify the same individuals? This question has captivated psychiatrists and psychologists since the inception of our disciplinechild* maltreatment, child* abuse, child* neglect, child bull*, child* trauma, child* advers*, and early life stress combined with prospective* and cohort.We performed a systematic review and meta-analysis in line with the PRISMA and MOOSE guidelines, following an a priori–defined protocol (eMethods and eTables 1 and 2 in the Two authors (J.R.B. and A.R.) independently screened titles and abstracts of all articles retrieved from the search before reviewing the full text of potentially eligible studies. We included original, peer-reviewed articles with prospectively collected information on childhood maltreatment (age <18 years). Measures of maltreatment , domestic violence, bullying, institutionalization, and broader measures of adverse childhood experiences that included maltreatment were used to define overall childhood maltreatment. From the articles with prospective assessment of childhood maltreatment, we selected studies with data on corresponding retrospective measures .Three authors  independently extracted data from all studies with prospective assessment of childhood maltreatment on sample characteristics , childhood maltreatment type(s) assessed, prospective measure type(s) , source , and availability of retrospective measures. If retrospective measures of childhood maltreatment were available, 2 authors (J.R.B. and A.D.) subsequently extracted data on the retrospective measurement type (interview or questionnaire) and source, agreement between prospective and retrospective measures, and study quality. Inconsistencies were resolved in consensus meetings and confirmed with the authors of the primary studies when necessary. Relevant missing information was requested from authors.The extracted data were converted to contingency tables comparing prospectively identified childhood maltreatment (yes or no) with retrospectively reported childhood maltreatment (yes or no). From the contingency tables, we derived estimates of prevalence, raw percentage of agreement between measures, and Cohen κ coefficient. Some studies only reported a κ. Prevalence and raw percentage of agreement estimates were used for descriptive purposes, and our primary outcome was the κ. The other extracted variables were used to explain the heterogeneity in the κs across studies.7 Data from contingency tables were first converted using the Freeman-Tukey double arcsine transformation8 to normalize and stabilize the variance of the sampling distribution, then aggregated using random-effects model meta-analyses, and finally back-transformed using the inverse of the Freeman-Tukey double arcsine transformation.8 To display the overlap between prospective and retrospective measures of child maltreatment based on these meta-analyses, we built Venn diagrams using the VennDiagram R package.9 To build Venn diagrams, we let the relative complements  vary while holding the intersection  constant.We first described the prevalence of childhood maltreatment based on prospective and retrospective measures of childhood maltreatment. We then examined the (1) prevalence of retrospective reports of childhood maltreatment among those with prospective observations, (2) prevalence of prospective observations among those with retrospective reports, and (3) raw percentage of agreement between the 2 measures through meta-analyses of proportions for different childhood maltreatment types with the metafor R package.10 The κs for each study were derived from contingency tables using the cohen.kappa command from the psych R package,11 which computes CIs based on the variance estimates discussed by Fleiss et al.12 The meta-analyses of κs were undertaken with the metafor R package using a random-effects model. When a study reported multiple effect sizes for different types of maltreatment, we calculated the mean of multiple κs to generate a single overall effect size for each study. We also undertook a sensitivity analysis selecting the largest κ from each study to assess the upper limit of agreement.Because the raw percentage of agreement can be inflated by chance, we derived a measure of agreement based on the κ, which accounts for chance findings and provides an estimate of variation in agreement in the population.7 First, we assessed heterogeneity between studies using the I2 statistic. Second, we assessed the presence of publication bias visually by funnel plot and formally by funnel plot–based tests, such as the Begg and Egger tests. Because these tests might be underpowered if only a few studies are available, we used a nonparametric trim-and-fill procedure to identify and correct for funnel plot asymmetry and reestimated the aggregate results. Third, we assessed the undue effect of individual studies on the meta-analysis results through jackknife sensitivity analyses, by testing changes in the estimate across permutations in which each study was omitted in turn.We next explored the effects of various possible sources of artifact or bias on κ estimates using the metafor R package.P < .05 was considered statistically significant.Finally, we tested predictors of heterogeneity in κs. We used subgroup analyses to test the contribution of measurement characteristics . We also used metaregression analyses to test the contribution of sample characteristics   with direct measures or paired data sufficient to compute measures of κs. Details of these studies are reported in the The study selection procedure is summarized in 31 Capitalizing on the paired nature of the data, we next analyzed (1) the prevalence of retrospective reports of childhood maltreatment among those with prospective observations, (2) the prevalence of prospective observations among those with retrospective reports, and (3) the raw percentage of agreement between prospective and retrospective measures. A random-effects meta-analysis of 7 studies32 focusing on a broad measure of child maltreatment revealed that the prevalence of retrospective reports among those with prospective observations was 48% ; the prevalence of prospective observations among those who retrospectively reported childhood maltreatment was 44% ; and the percentage of agreement between prospective and retrospective measures of childhood maltreatment was 76% . Therefore, on average, 52% of individuals with prospective observations of maltreatment did not retrospectively report it, and 56% of individuals retrospectively reporting maltreatment did not have concordant prospective observations ; the prevalence of prospective observations among those who retrospectively reported childhood sexual abuse was 25% ; and the percentage of agreement between prospective and retrospective measures of childhood sexual abuse was 86% . Second, the prevalence of retrospective reports among those with prospective observations in the 9 studies31 that included childhood physical abuse was 38% ; the prevalence of prospective observations among those who retrospectively reported childhood physical abuse was 42% ; and the percentage of agreement between prospective and retrospective measures of childhood physical abuse was 75% . Third, the prevalence of retrospective reports among those with prospective observations in the 4 studies28 that included childhood emotional abuse was 37% ; the prevalence of prospective observations among those who retrospectively reported childhood emotional abuse was 15% ; and the percentage of agreement between prospective and retrospective measures of childhood emotional abuse was 76% . Finally, the prevalence of retrospective reports among those with prospective observations in the 4 studies25 that included childhood neglect was 23% ; the prevalence of prospective observations among those who recalled childhood neglect was 18% ; and the percentage of agreement between prospective and retrospective measures of childhood neglect was 84% .We next undertook sensitivity analyses to test whether the overlap between individuals identified as maltreated through prospective or retrospective measures varied as a function of the type of maltreatment . First, P < .001; I2 = 93%). A forest plot displaying the meta-analytic findings is reported in Because the raw percentage of agreement can be inflated by chance, we next examined the agreement between prospective and retrospective measures based on the κ, which accounts for chance findings and provides an estimate of variation in agreement in the population. A random-effects model meta-analysis of the 16 studies that included any measure of maltreatment revealed that the agreement between prospective and retrospective measures of childhood maltreatment was poor, with κ = 0.19  and association between effect sizes and corresponding sampling variances . To correct for funnel-plot asymmetry arising from publication bias, we used a trim-and-fill procedure. The trim-and-fill results with 17 studies  . Second, we considered whether the measure used for retrospective assessment of maltreatment could explain heterogeneity in effect sizes. As shown in P = .04). An overall test of moderation showed that retrospective measure type explained the heterogeneity in agreement . Third, we tested whether the type of childhood maltreatment could explain heterogeneity in effect sizes. As shown in eFigure 4 in the df = 1; P = .04), indicating that smaller samples had higher agreement between prospective and retrospective measures. However, we did not find that heterogeneity in agreement was explained by other characteristics of the samples, such as sex  or age at retrospective report . Variation in study quality also did not explain heterogeneity in effect sizes  , reports , or mixed measures . An overall test of moderation showed that prospective measure type did not explain the heterogeneity in agreement  or by fabricating information .35 and constraints on reliability add error variance, ultimately reducing agreement between prospective and retrospective measures.36 Second, low agreement may be due to systematic differences in the sensitivity of the measures  , the reporting period23 , or the definition of the maltreatment experience between prospective and retrospective measures19 .Measurement features can also reduce agreement in several ways. First, all childhood maltreatment measures have imperfect test-retest reliability,37; (2) deficits in consolidating the maltreatment memory owing to low emotional valence 38 or disrupted sleep patterns39; (3) deficits in reconsolidating the maltreatment memory owing to memory updating during subsequent reactivation if false feedback is given40 , if the memory is no longer associated with distressing emotions ,41 or if reappraisal is positively biased by personality features 23; (4) deficits in memory storage owing to brain injury or aging42; or (5) deficits in retrieving the maltreatment memory owing to infantile amnesia,43 forgetting ,44 or cognitive avoidance strategies to regulate affect.47 On the other hand, overreporting may occur because of (6) bias in memory encoding or reconsolidation owing to individual suggestibility  or a source-monitoring error 49 or (7) inaccurate retrieval linked to negative bias in autobiographical memory .50Finally, memory biases can reduce agreement by promoting underreporting and overreporting of actual experiences. On the one hand, underreporting may occur because of (1) deficits in encoding the maltreatment experience in early life owing to immature, delayed, or impaired brain development51 Second, agreement was also higher in studies with smaller samples .52 the low agreement between prospective and retrospective measures cannot be interpreted to directly indicate poor validity of retrospective measures. For example, prospective measures may have lower sensitivity , and the higher prevalence of retrospective measures could, thus, indicate greater ability to identify true cases of childhood maltreatment. If that was the case, predictions from retrospective measures should converge on the same outcomes as those of more specific prospective measures , and retrospective measures should not only be associated with outcomes assessed with the same method  but should also be associated with outcomes assessed with other methods, such as objective measures .53 A few studies25 have tested these questions and have observed that prospective and retrospective measures assessed in the same individuals are associated with similar outcomes. However, retrospective measures showed stronger associations with self-reported outcomes than objectively assessed outcomes,31 raising concerns about potential common method bias.54 Therefore, further research in other samples is needed to comprehensively evaluate the construct validity of retrospective measures. Regardless of any concerns regarding their validity, retrospective reports may still be pragmatically used in the clinic as risk indicators associated with incidence of psychopathology, its course of illness, or treatment response.55Third, although prospective measures are generally considered to be more valid (specific) indicators of the occurrence of maltreatment,Our findings have implications for researchers and health care professionals. Although retrospective reports and prospective measures identify at-risk individuals, the groups of individuals identified with either measure are not the same . Therefo


West Nile virus (WNV), a small, positive sense, single stranded RNA virus continues to encroach into new locales with emergence of new viral variants. Neurological disease in the equine can be moderate to severe in the face of low to undetectable virus loads. Physical methods of virus enrichment may increase sensitivity of virus detection and enhance analysis of viral diversity, especially for deep sequencing studies. However, the use of these techniques is limited mainly to non-neural tissues. We investigated the hypothesis that elimination of equine brain RNA enhances viral detection without limiting viral variation. Eight different WNV viral RNA enrichment and host RNA separation methods were evaluated to determine if elimination of host RNA enhanced detection of WNV and increase the repertoire of virus variants for sequencing. Archived brain tissue from 21 different horses was inoculated with WNV, homogenized, before enrichment and separation. The protocols utilized combinations of low-speed centrifugation, syringe filtration, and nuclease treatment. Viral and host RNA were analyzed using real-time PCR targeting the WNV Envelope (E) protein and equine G3PDH to determine relative sensitivity for WNV and host depletion, respectively. To determine the effect of these methods on viral variation, deep sequencing of the E protein was performed. Our results demonstrate that additional separation and enrichment methods resulted in loss of virus in the face of host RNA depletion. DNA sequencing showed no significant difference in total sequence variation between the RNA enrichment protocols. For equine brain infected with WNV, direct RNA extraction followed by host RNA depletion was most suitable. This study highlights the importance of evaluating viral enrichment and separation methods according to tissue type before embarking on studies where quantification of virus and viral variants is essential to the outcome of the study. West Nile virus (WNV) was introduced to North America resulting in more than 49,794 human infections with 4% mortality, 28,063 equine infections, and over 100,000 avian population infections  compared to horses . Moreovehe brain . Often iSince WNV virus is difficult to detect in the equine, physical enrichment methods may be of use when extracting equine brain tissues. Yet, there are limited studies on physical enrichment techniques in a complex cellular milieu such as the equine brain , 19. TheSeveral quick and established methods to separate viral RNA from host RNA include low-speed centrifugation, filtration, freeze-thaw, nuclease treatment, and combinations of these methods can also enhance extraction efficiency –22. The We investigated the hypothesis that elimination of equine brain RNA enhances viral detection without limiting viral variation. The goal of this study was to identify the effect of RNA enrichment methods on the amount and diversity of WNV RNA using inoculated fresh equine brain tissue. This study methodically investigated eight different methods to physically enrich viral RNA so that it would be concentrated for detection and sequencing without creating bias in virus variation.4 PFU/mL of WNV NY99 (GenBank accession AF260967) using a blunt needle. This dose was chosen since horses develop titers of 104−106.8 PFU/mL in the brain via tissue culture, if detected at all in a specific region , host RNA depletion (R) using a commercial kit , low speed centrifugation (C) at 6000 × g at 4°C for 10 m , sterileRNA was converted into cDNA using a commercial kit  and addition of oligo dT's  according to the manufacturers' protocols. The copy numbers of WNV Envelope (E) gene and equine G3PDH gene were measured using real-time PCR Table  as previFour samples were randomly selected from each treatment group. Because WNV is present in low virus quantities in natural infection, PCR amplification prior to sequencing was performed to simulate conditions that may be need for phylogenetic studies of clinical WNV horses. Fragments of cDNA were amplified using conventional PCR Table . The PCRp-value, type of variants, and frequency of variants  . Brieflyvariants .p < 0.05 was considered significant . The Games-Howell pairwise comparison test was used to detect differences between groups. In order to analyze whether the frequency of variation was affected by an extraction method, variation was grouped into one of four classifications based on the frequency of observation for that variant, with levels defined as 0–0.5, 0.5–1, 1–5, and 5–50% of the total variants. Differences were then analyzed by multiple regression analysis (p < 0.05) with treatment and frequency classification as predictor or dependent variables.WNV E protein and G3PDH gene expression, RIN, mapped reads, and total variation, were compared between all treatments groups using Welch's ANOVA where p = 0.002). The highest mean RIN was detected in group T (RIN 6.65) and the lowest mean RIN was detected in group CTR . Low average RIN numbers were measured from treatment groups TR, CTR, and CSNTR with average RINs of 2.3, 2.024, and 2.475, respectively. High average RIN numbers were measured from groups T (RIN 6.65) and CT (RIN 5.275), while the CSNT, CSTR, and CST treatment groups showed intermediate RNA quality with RINs ranging from 3.2 to 4.8.The RIN is an algorithm for assessing the integrity values of the RNA . The RINp = 0.001).The treatment groups with RNA depletion with selective depletion of host ribosomal RNA  had significantly lower RIN numbers compared to the groups which did not have the host RNA depletion treatment  (p = 0.001). The treatment groups with low copy numbers for both WNV E protein and G3PDH were from groups CTR, CSTR, and CSNTR   Figure . The CST) Figure . The agrp = 0.185) . The TR, CSNT, and CSNTR groups had the highest mean total virus variation but this difference was not significant p = 0.18 (Figure The frequency of variation was categorized into four levels including 0–0.5, 0.5–1, 1–5, and 5–50%. In all groups, the mean number of observations was statistically higher in the 0–0.5% frequency classification across all treatment groups Figure  and therThe goal of this study was to identify RNA enrichment methods for the WNV infected equine brain with the hypothesis that the viral enrichment would increase the detection sensitivity and that viral diversity would be maintained or enhanced. The overall goal of this research was to determine which technique would be most applicable to extraction of tissues from the clinically diseased horse. We purposely chose this experimental design to control for the variation expected if experimentally or naturally infected animals were used, in order to establish a technical protocol for intrahost phylogenetic studies. This allowed us to determine, without bias, the best methods for obtaining consistent virus RNA for downstream sequencing experiments to contribute to the newly emerging field of phyloanatomy , 35. In Real-time PCR results showed that phase extraction only resulted in the highest WNV E protein gene and equine G3PDH copy numbers. Clearly, extraction technique could affect the sensitivity of detection of WNV nucleic acids, which has implications for diagnostic testing. What is unknown is if viral sensitivity is altered with incorporation of various commercial RNA extraction kits.The amount of WNV E protein and equine G3PDH decreased with fewer enrichment treatments likely indicating a lack of separation of virus from host tissues. Since this model used inoculation without infection, a portion of intracellular virus would also likely be depleted with more separation with more separation with actual infection. Additive methods such as low speed centrifugation, syringe filtration, nuclease treatment, and host RNA depletion had no obvious improvement in terms of viral variant analysis or for detection purposes. Even host cell depletion alone resulted in a profound loss of viral RNA. However, these results must be interpreted in the context of the specific virus and sample.Groups TR, CTR, CSTR, and CSNTR had lower WNV E protein and G3PDH copy numbers per microliter compared to the other four treatment groups. The difference between these treatment groups was the host RNA depletion treatment. The host RNA depletion kit used was designed for human, mouse, and rat samples and may not work as well in equine or neural tissues. For virus detection, group T was the best method as the DNA copy number for WNV E protein and G3PDH amount was the greatest compared with the other treatment groups.WNV virus sequence variations were significantly different between treatment groups and the TR group had the highest average number of variants detected in the samples. Group T could be considered for RNA extraction since it had the highest WNV E protein RNA recovery and will be an important consideration where virus is minimally detectable. Notable is the amount of variation in sequence introduced in the CSTR and CSNTR, which will have an effect on the ability to detect significant differences in variation between samples.Methods that separate host materials from pathogens have been investigated for RNA viruses and are important for viral discovery and deep sequencing studies. However, there are few studies that provide conclusive evidence that host genome depletion enriches for viral RNA in a manner that sensitivity of viral detection is enhanced or that investigation of viral variation is improved for brain –22. SomeWe incorporated PCR into this protocol because prior literature indicates inconsistent results in sequencing output in the face of positive real time rtPCR results in equine WNV infection . This isStudies comparing direct deep sequencing with prior amplification would be required to investigate the effect of PCR on viral variation for this particular virus in equine brain. For this type of study, an experimental design incorporating clinical and/or experimentally infected horses would be appropriate.This study highlights the risk of using enrichment treatments without consideration of the virus target and the sample type. Additive methods beyond host cell depletion had no obvious improvement in terms of viral variant analysis or viral detection; for example, host cell RNA depletion resulted in a profound loss of viral RNA. Evaluation of viral enrichment and separation method appropriate for the sample type is important for viral detection and later sequencing.This study was carried out in accordance with the recommendations of the University of Florida Institutional Animal Care and Use Committee.DP, TW, MS and ML designed the study. DP, JL, and NW performed necropsy of the equines and confirmation of post-mortem findings. DP performed RNA extraction, real-time PCR testing, and sequencing. DP, ML, and KB performed data auditing and analysis. TW provided sequencing service and consultation. MD and AB assisted in sequencing data analysis. DP wrote the manuscript draft while the other authors edited the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Quercus robus and Quercus petraea) bark tissue for subsequent high-throughput sequencing. In addition, reducing the quantity of bark tissue used for an established protein extraction protocol yielded high quality protein for parallel analysis of the oak-microbiota metaproteome. These procedures demonstrate the successful extraction of nucleic acids and proteins from oak tissue using as little as 50 mg of sample input, producing sufficient quantities for nucleic acid sequencing and protein mass spectrometry of tree stem tissues and their associated microbiota.The application of high-throughput nucleic acid and protein sequencing technologies is transforming our understanding of plant microbiomes and their interactions with their hosts in health and disease. However, progress in studying host-microbiome interactions in above-ground compartments of the tree (the phyllosphere) has been hampered due to high concentrations of phenolic compounds, lignin, and other compounds in tree bark that severely limit the success of DNA, RNA, and protein extraction. Here we present modified sample-preparation and kit-based protocols for the extraction of host and microbiome DNA and RNA from oak ( Quercus robur and Quercus petraea) [Advances in nucleic acid sequencing and proteomics technologies have revolutionized our ability to study the biology of plant hosts and their associated microbiota ,2,3. Whipetraea) ,7. Thesepetraea) ,7. The aDNeasy Plant Mini kit Qubit dsDNA HS assay kit NEBnext microbiome DNA enrichment kit Genomic DNA Clean and Concentrator kit w/v) polyvinylpyrrolidone, and 1% (v/v) β-mercaptoethanol)RNA extraction buffer DNease I (Qiagen)RNeasy MinElute Cleanup kit (Qiagen)Ribo-Zero ribosomal RNA (rRNA) Removal kits for plant seed/root and for bacteria Qubit RNA HS assay kit (Thermo Fisher)Protein solubilization buffer Ice cold 20% trichloric acid in acetone with 0.5% DTTIce cold acetone3% SDS solutionDNA extraction Use approximately 50 mg of oak tissue homogenized with a mortar and pestle under freezing conditions in liquid nitrogen. Transfer homogenized tissue into DNA extraction kit tube.Use the DNeasy Plant Mini kit (Qiagen) according to the manufacturer’s instructions.In order to enrich microbiome DNA, deplete the host DNA from the sample using the NEBnext microbiome DNA enrichment kit (New England Biolabs) according to the manufacturer’s instructions.Purify the DNA and concentrate using the Genomic DNA Clean and Concentrator kit (Zymo Research) according to the manufacturer’s instructions.Store at −20 °C.RNA extraction , RNeasy MinElute Cleanup kit (Qiagen), and Ribo-Zero ribosomal RNA (rRNA) Removal kit reaction ).w/v) polyvinylpyrrolidone, and 1% (v/v) β-mercaptoethanol) is added to oak tissue kept frozen in a sterilized mortar using liquid nitrogen. The volume of extraction buffer used at this step was increased from the original protocol, as lower volumes of 1−2 mL were not sufficient to produce a significant quantity of RNA.Bark samples collected for transcriptome analysis were immediately frozen in liquid nitrogen for on-site preservation of RNA. For RNA extraction, use approximately 50 mg of oak tissue homogenized with a mortar and pestle under freezing conditions in liquid nitrogen. Briefly, 5 mL of extraction buffer . The incubation time has been increased while the shaking intensity has been decreased in comparison to the original protocol.After centrifugation in the QIAShredder column, mix 350 µL of the supernatant with 0.9 volumes of ethanol instead of 0.5 according to the kit protocol, and subsequently follow the manufacturer’s protocol by centrifuging in the RNeasy Mini column.The manufacturer’s instructions for the RNeasy Plant Mini kit are followed from this stage onwards.Treat the extracted RNA with DNase I (Qiagen) following the RNeasy Plant Mini kit (Qiagen) instructions for DNase treatment.The RNA is purified using the RNeasy MinElute Cleanup kit (Qiagen) following the manufacturer’s instructions.Deplete rRNA from RNA extracts using a 1:1 combination of the Ribo-Zero rRNA Removal kits for plant seed/root and for bacteria (Illumina) according to the manufacturer’s instructions.Purify the rRNA depleted samples again using the RNeasy MinElute Cleanup kit (Qiagen) and store at −80 °C.Protein extraction .Use approximately 50 mg of oak tissue homogenized with mortar and pestle under freezing conditions in liquid nitrogen. A lower amount of bark tissue is used than in the original protocol (50 mg instead of 300 mg lyophilized powdered bark tissue) due to high levels of proteases and phenolic compounds.Add 2 mL solubilization buffer  and grind in a mortar and pestle at room temperature.Shake the mixture on a platform shaker (150 rpm) for 1 h at ambient temperature.Centrifuge samples at 20,000 g for 20 min and extract and store the supernatant at 4 °C. Repeat the procedure using the remaining pellet.Extract the supernatant again and pool with the previous supernatant.Add ice cold 20% trichloric acid in acetone with 0.5% DTT in a 1:1 ratio to the supernatant pool and precipitate at −20 °C overnight.g for 60 min and wash with ice cold acetone .After precipitation, centrifuge the mixture at 20,000− Air-dry the pellet, re-suspend in 3% SDS solution and store at −80 °C.The methods described here were used for our previous DNA/RNA sequencing and shotgun proteomic analysis of microbiota associated with healthy oak trees and oak affected by Acute Oak Decline ,6. The qFor RNA extraction, we modified a protocol presented by Kalinowska et al. (2012) where a pre-extraction kit process is performed to remove inhibiting compounds, mixing bark tissue with a buffer containing polyvinylpyrrolidone, β-mercaptoethanol, and EDTA under freezing conditions . The maiThe resulting nucleic acid eluates (DNA and RNA) were successfully sequenced on the Illumina HiSeq 2500 platform, producing tens of millions of high-quality reads per sample . The pro