This achievement greatly improved the sensitivity of the assay over previous versions. In summary, this constructed RT-qPCR assay may be considered a promising tool for providing accurate information on very low HIV-1 RT activity. Based on previous experience in our laboratory, we developed a real-time reverse transcriptase (RT) quantitative PCR (RT-qPCR) assay for the assessment of very low levels of HIV-1 RT activity. The RNA, acting as a template for reverse transcription into cDNA by HIV-1 RT, consisted of a synthetic RNA ad hoc generated by in vitro transcription and included a coding sequence for HSV-1 gD (gD-RNA-synt). Different conditions of variables involved in the RT-qPCR reaction, notably different amounts of gD-RNA-synt, different mixes of the reaction buffer, and different dNTP concentrations, were tested to optimize the assay. The results indicated that the gD-RNA-synt-based RT assay, in its optimized formulation, could detect a specific cDNA reverse transcription even in the presence of 1 × 10 Assays based on the evaluation of the activity of the RNA-dependent DNA polymerase, the reverse transcriptase (RT) enzyme that characterizes all retroviruses ,2, were We have recently demonstrated the potentialities of a real-time RT quantitative PCR assay to quantitatively measure the enzymatic activity of HIV-1 RT directly at the plasmatic level to screen for the functional status of HIV-1 in PLWH . This asStable transfected I143tk- cells, ectopically expressing the US6 gene of herpes simplex virus 1 (HSV-1) and encoding for glycoprotein D (gD), already available at our laboratory, were cultivated as previously described . These c5 cells/well. After 24 h of incubation at 37 °C, the cells were trypsinized, washed with PBS, and collected in ice for total DNA extraction using the commercial Quick-DNA Microprep Plus Kit (Zymo Research). The obtained total DNA, containing the expressing vector for gD, identified as pcDNA-J3, was quantified by a NanoDrop 2000 Spectrophotometer  and then amplified with the T7 promoter primer (T7pw) and the gDc9Rev primer. As a control, samples without the template  were used. In addition, a parallel amplification was set up using the oligo gDc9Fw designed on a US6 internal sequence as a forward primer. The sequences of the selected primers and the expected sizes for the related amplicons are shown in The main strategy pursued during the present study was the substitution of total RNA extracted from cells stably expressing the HSV-1 gene for gD with a synthetic RNA containing genetic information for the same gene (gD-RNA-synt) as a template for the reverse transcription reaction. For this purpose, three main operational phases were carried out: (i) generation of amplicons containing a portion of the US6 gene for gD and the promoter sequence for the T7 RNA polymerase to utilize as DNA templates for in vitro transcription, (ii) in vitro transcription by T7 RNA polymerase, and (iii) purification of the generated specific gD-RNA-synt molecule. To prepare the DNA template containing the T7 promoter sequence upstream to the initial portion of the coding sequence for the US6 gene (GeneBank accession number L09242.1.), I143-J3 cells, controlled for HSV-1 gD expression by indirect immunofluorescence using a specific anti-gD antibody , were seeded at a density of 5 × 10http://www.ncbi.nlm.nih.gov/tools/primer-blast/, accessed on 15 March 2022). The options returned by Primer-BLAST were analyzed for their structural and thermodynamic characteristics using NetPrimer software  and OligoFaktory  and then controlled for their specificity by means of single BLAST . PCR amplification was performed in 25 μL with 200 nM of each primer, 0.25 mM dNTP mix, and 1×PCR buffer with 1.5 mM MgCL2 and 0.5 U of AmpliTaq Gold™ DNA polymerase . The PCR conditions were 95° for 10 min, followed by 35 cycles of 95° for 15 s, 58° for 30 s, and 72° for 45 s. The PCR products were run on a 1.5% agarose gel to confirm the size of the amplicons. Next, in vitro transcription was performed with the MEGAScript T7 Transcription kit . Each 20 μL reaction contained 2 μL of 10×buffer, ATP, CTP, GTP, UTP, T7 RNA polymerase, and 100 ng (~2 µL) of T7-tagged amplicon. After incubating at 37° for 3 h, the DNA was digested with 2 U of TURBO-DNase at 37 °C for 15 min. The in vitro transcribed RNA was subsequently purified by a MEGAclear kit (Ambion Cat no AM1908), eluted in 30 μL of DEPC-dH2O, aliquoted, and stored at −80 °C. As a control, in parallel, a reaction was set up with 1 µg of linearized pTRI-Xef plasmid, supplied in the kit. Quantitation of the RNAs was performed spectrophotometrically at 260 nm by the NanoDrop 2000. The gD-RNA-synt concentration was measured in duplicate, and the concentration was then converted to the molecule number using Avogadro’s number.The primers were designed to obtain a maximum amplicon size of 650 bp using Primer-BLAST  the basic procedures have been described in detail in previous publications and (ii) the various variables utilized during the selection phases are described in detail in the “Results”, the methodology of the RT-qPCR assay, in its optimized protocol, will be only briefly described here.6 molecules of in vitro transcribed RNA were mixed with 1 µL of 10× homemade RT Buffer, named “TriB 1.5” , 500 nM of gD-specific reverse primer (5′-GCATTCGGTGTACTCCATGAC-3′), 0.1 mM of each dNTP, and 1 µL of the stated dilution of HIV RT in a total volume of 10 µL. The mixture was set up on ice and then incubated for 240 min at 37 °C and 5 min at 85 °C. The resulting cDNA was stored at −20 °C.Synthesis of cDNA was performed from gD-RNA-synt as a template using different amounts of a commercial recombinant HIV-1 RT . Specifically, 10In the second step of the assay, real-time quantitative PCR was performed on an Applied 7500 System instrument. Amplification of specific PCR products was detected using the Maxima SYBR Green/ROX qPCR 2X Master Mix . Each real-time PCR reaction was performed in MicroAmp 96-well PCR plates (Applied Biosystems™) in a total reaction volume of 25 μL containing 1 X SYBR Green Mix, 10x diluted Rox solution, 0.5 U of UDG (Thermo Scientific) 300 nM forward  and reverse  primers, and 1 µL of the first step dD-specific cDNA product. PCR cycling was performed as follows: 2 min at 50 °C (UDG pretreatment), 10 min at 95 °C, followed by 40 rounds of 15 s at 95 °C and 60 s at 60 °C. A melting curve  was generated to verify the specificity of the primer amplification.To monitor the possible sampling error and experimental error, three experiments with three technical qPCR replicates for each RT sample were independently performed, unless otherwise indicated. Quantifications shown in the figures represent the mean values and standard deviation (S.D.) of the means calculated for the representative experiments shown in the graphics. Nonlinear regression analysis was performed using GraphPad Prism v.6.01 software .The main objective of the present study was the development of an ultrasensitive assay that could be utilized for the analysis of low levels of HIV-1 RT enzymatic activity. The actual technical challenge was detecting the retrotranscriptional activity of HIV-1 RT by an RT-qPCR assay, even when the enzyme was present in minimal quantities in the reaction mixture. Moreover, a mandatory requirement was the simplicity of execution that characterized the two-step RT-qPCR assay previously drawn up by us. In the previously described assay, total RNA extracted from human cells stably transfected with the US6 gene for gD of HSV-1 was utilized as the source of the exogenous RNA template to be retrotranscribed. Differently for the new assay, a specific RNA molecule, drawn on the sequence of a portion of the same US6 HSV-1 gene, was generated in vitro as the RNA template for the reverse transcription reaction. In fact, the presence of a unique RNA species in the reaction mixture was considered a favorable condition in the case of very low RT concentrations. For this purpose, a DNA template containing a portion of the selected gene and provided with the T7 promoter sequence for the RNA polymerase was generated. The design and choice of the oligonucleotide sequences to be used took into account the following conditions: (i) the portion of the US6 gene to be amplified should not be less than 400 bp or greater than 800 bp to remain in an optimal length range for in vitro transcription using T7 RNA polymerase; (ii) the region to be amplified had to contain the portion of US6 recognized by the primer pair already used for the previously validated SYBR Green RT-qPCR to allow a direct comparison between the previous conditions and the current strategy; and (iii) the presence of the T7 promoter upstream of the specific US6 sequence located should be recognized by the T7 RNA polymerase. The pcDNA 3.1 vector carrying the US6 gene for gD of the I143-J3 cells  includedA volume of 2 μL of the PCR reaction was added as the DNA template in a volume of 20 μL in vitro transcription reaction set up with the bacteriophage T7 RNA polymerase and reagents from a commercial kit. In parallel, a linearized pTRI-Xef plasmid supplied in the kit was transcribed as the reaction control. Following the in vitro transcription, DNase was added to digest the DNA template, and the mixtures were purified by affinity RNA columns. Then, the in vitro transcribed RNA molecules corresponding to the selected region of the US6 gene for HSV-1 gD (gD-RNA-synt) were further analyzed by a 5% acrylamide/8M urea denaturing gel. As shown in 9 molecules/μL and corresponding to 300 pg/μL of purified gD-RNA-synt, three tenfold dilutions were prepared and tested as a volume of 1 μL each. Samples containing the different amounts of gD-RNA-synt were incubated at 37 °C for 1 h in the presence of 1 × 10−2 U of HIV RT, according to the retrotranscription protocol. As a control, samples without the RT enzyme were set up. At the end of the retrotranscription reaction, 1 μL of the produced cDNA was used for real-time PCR quantification. The results indicated that using gD-RNA-synt as a template enabled obtaining good quantities of retrotranscribed cDNA even in the presence of 1 × 10−2 U of HIV RT and that using an amount of 107 or 106 molecules/μL of gD-RNA-synt in the mixture resulted in no amplification in the corresponding RT-minus samples. Using, instead, an amount of 108 molecules/μL of gD-RNA-synt occasionally gave an amplified DNA at very high threshold cycles, in repeated tests in the RT negative controls , corresponds to the RT present inside about three virions. Nevertheless, there are many uncontrollable factors that could influence an RT-based real-time PCR reaction working at its limit of detection. In fact, even in our experiments not all the replicated samples, during the various phases of the setting up of the assay, ensured exactly the same limit of detection. This is the reason why in this phase of the study, different to other authors, we preferred to limit our experiments to a maximal dilution of HIV-1 RT to 10−9 U to avoid exceeding the limit of an average Ct of 35 to evaluate the reliability of the assay. All this makes it possible to assert that the new assay has high sensitivity and a very simple and quick execution mode.The present study reports the technical details of the setting up of an assay to provide information on the enzymatic activity of HIV-1 RT, even in the presence of small amounts of the viral enzyme. Our study was carried out taking into account our previous experience in the specific fields ,45,46. TInformation on the replication-competent status of residual viremia is a main objective in the management of PLWH treated with ART. In fact, the main purpose of antiretroviral therapy is a lasting suppression of viral replication up to potentially undetectable plasmatic levels. This end point should ensure the delay of the possible recrudescence of the disease and to prolong the life expectancy and quality of life of PLWH. The availability of increasingly sensitive assays capable of effectively detecting even small amounts of replicating viruses is, therefore, a fundamental aspect of current anti-HIV strategies. Among the different assays, the amplification of the RNA of the HIV virions present in the serum represents the most widespread and validated strategy. This method, however, while representing the gold standard assay for the evaluation of VL, might have some limitations in providing, by itself, exact information on the real replicating status of residual or blipping viremia. In fact, comprehensive information on the replication-competent status of the HIV-1 reservoir in PLWH is far from being easily ascertained. Thus, detection of HIV-1 RT activity even in the presence of small amounts of the viral enzyme could possibly have the requirements to meet these needs.In conclusion, the RT-qPCR assay described here, using a gD-RNA-synt as a template for the first time, may be considered right now as an additional tool for basic or translational studies devoted to the accurate evaluation of very low levels of HIV-1 RT. Among these, of particular interest are those aimed at selecting new antiviral strategies by screening even more effective and tolerable compounds in vitro. Moreover, the assay could also represent a promising basis for furnishing information on the functional virological status of PLWH. In fact, the results showed that the RT detection limit of the new version of our assay corresponds to the amount of enzyme contained in three viral particles. Future studies, however, using plasmatic samples from HIV-1 infected patients as a source of RT are necessary. Only the results of these studies will confirm whether this RT-qPCR assay may represent a valid methodological optimization for the detection of small quantities of HIV RT enzyme in PLWH.


Thermus thermophilus RNAP EC engaged with Rho. The Rho hexamer binds RNAP through the carboxyl-terminal domains, which surround the RNA exit site of RNAP, directing the nascent RNA seamlessly from the RNA exit to its central channel. The β-flap tip at the RNA exit is critical for the Rho-dependent RNA release, and its deletion causes an alternative Rho-RNAP binding mode, which is irrelevant to termination. The Rho binding site overlaps with the binding sites of other macromolecules, such as ribosomes, providing a general basis of gene regulation.Transcription termination is an essential step in transcription by RNA polymerase (RNAP) and crucial for gene regulation. For many bacterial genes, transcription termination is mediated by the adenosine triphosphate–dependent RNA translocase/helicase Rho, which causes RNA/DNA dissociation from the RNAP elongation complex (EC). However, the structural basis of the interplay between Rho and RNAP remains obscure. Here, we report the cryo–electron microscopy structure of the  Cryo-EM captures the structure of an RNA polymerase elongation complex engaged with the termination factor Rho. From bacteria to eukaryotes, DNA-dependent RNA polymerase (RNAP) conducts gene transcription via three sequential processes—initiation, elongation, and termination. The termination process includes the stalling of the transcribing RNAP elongation complex (EC) at termination sites within a gene, followed by RNA and DNA dissociation from RNAP to generate the proper RNA 3′ end. Two termination mechanisms have been elucidated: intrinsic termination that does not require any auxiliary factors and factor-dependent termination that requires one or more specific protein(s) for termination (Rho is an adenosine triphosphate (ATP)–dependent RNA translocase/helicase with 5′ → 3′ directionality  and NusA. These structures suggested that Rho induces an allosteric change in RNAP to destabilize the EC for priming the dissociation of RNA and DNA. However, these studies also postulated that termination ultimately involves the Rho ring closure and its engagement with RNA, followed by the Rho translocation to release RNA and DNA. In this study, we recapitulated the Rho-associated EC using proteins from the bacterium Thermus thermophilus and performed structure determination by cryo-EM single-particle analysis. The structure revealed the manner by which the nascent RNA-engaged Rho hexamer in the closed-ring conformation interacts with the RNA exit site of RNAP, illuminating the EC state before termination.Cryo–electron microscopy (cryo-EM) structures of T. thermophilus Rho and RNAP. A 199–base pair (bp) DNA containing a 114-bp G-less segment was designed, and one end of the DNA was immobilized on a magnetic bead (4) or ADP–beryllium fluoride (ADP·BeF3).To examine the Rho-dependent RNA release activity from the RNAP EC, we developed an in vitro experimental system using tic bead . The RNAE. coli Rho, T. thermophilus Rho also prefers C-rich sequences . The A-less template was also constructed by replacing A in the G-less segment by G. The RNA release with the C-less template was deficient , suggestE. coli, the transcription elongation factor NusG directly binds Rho and enhances Rho-dependent termination . NusG had no effect on the Rho-dependent RNA release (fig. S1C), and therefore, we omitted NusG in this study. In our in vitro transcription system, GreA, which helps to reactivate a backtracked EC . By the initial two-dimensional (2D) classification, the particles were classified into the Rho-only and RNAP-containing classes  [Protein Data Bank (PDB) 5JJI] . The purified EC was mixed with Rho in the presence of ADP·BeFThe particles containing RNAP were further sorted by 3D classification into DNA/RNA-unbound RNAP (apo RNAP), EC, and two forms of RNAP-Rho complexes (referred to as the type 1 and type 2 complexes) (figs. S3 and S4). The EC holds a transcription bubble containing a 10-bp DNA/RNA hybrid within the RNAP main channel  and 2. TT. thermophilus Rho  of the six residues that recognize the pyrimidine nucleotides in E. coli Rho (PDB 1PVO) (T. thermophilus Rho (fig. S5C). Therefore, one possible explanation for the absence of RNA density in the PBS is that the RNA binding by T. thermophilus Rho might be weaker than that by E. coli Rho. Alternatively, the C-rich sequence may only be required for the Rho loading step and dispensable after the Rho ring closure and engagement with the EC.In the type 1 complex, the Rho hexamer assumes a closed-ring conformation and is engaged with the EC  (The β-flap domain of the RNAP β subunit (residues β762 to β784) forms part of the RNA exit channel. The tip helix of the β-flap domain is reoriented and adapted to the C-terminal side of a Rho protomer  is inserted into the Rho NTD (Rho_T4L70 and Rho_T4L115) . As the T. thermophilus (the type 1 complex). In this structure, the Rho hexamer is in a closed-ring conformation and engaged with the RNA and EC. The Rho hexamer binds to the rim of the RNA exit channel of EC via its CTD side and seamlessly threads the emerging nascent RNA into its central channel. Our results demonstrated that the β-flap tip, which forms part of the RNA exit channel, is essential for the Rho-EC engagement and the Rho-dependent RNA release. Thus, Rho binding by the EC is mediated by both the nascent RNA and the specific Rho-RNAP interaction, consistent with the “classic” view of Rho-dependent transcription termination , in which Rho binds near the DNA exit site of apo RNAP through its NTD side. The T4L insertions into the NTD did not affect the RNA release activity of Rho. Moreover, the deletion of the RNAP β-flap tip, which is critical for the Rho-dependent RNA release, enhanced the formation of the type 2 complex. Therefore, the inverted Rho-binding mode in this complex is unlikely to be relevant to termination. The abundance of the type 2 complex in the cryo-EM particles suggests that Rho may preferentially bind apo RNAP in this alternative mode. Therefore, this complex could potentially resemble a posttermination state formed after the EC has released DNA and RNA.E. coli Rho-RNAP complex structures, Rho was bound near the DNA exit site of the EC through its NTD side, as in our inverted Rho-RNAP structure (the type 2 complex) (fig. S9)  of RNAP and NusA. While the authors of these studies postulated that the Rho-RNAP interaction induces allosteric changes in the EC active site, they also proposed that transcription termination occurs via its subsequent state, in which Rho assumes a closed-ring conformation to gain access to both the nascent RNA and the RNA exit channel of RNAP. Our current structure of the Rho-engaged EC (the type 1 complex) might have captured this state.In previous studies of E. coli   and pET-47b (ω subunit) vectors. These plasmids were coexpressed in E. coli Rosetta2 (DE3). Plasmids for the expression of RNAP variants were constructed on the basis of these plasmids. In ΔβFL and ΔZBD, the β-flap tip helix (residues β762 to β782) and the zinc binding domain (residues β′57 to β′80), respectively, were removed, and the gaps were filled with three alanine residues. In βFL3K, residues Leu773, Ile777, and Phe778 of the β subunit were replaced by lysine residues. The recombinant RNAP variants were purified as described previously . The cells were suspended in lysis buffer A  and disrupted by sonication. The lysate was heated at 70°C for 10 min to denature the E. coli proteins, and the precipitate was removed by centrifugation. The supernatant was loaded onto a Ni affinity column . The column was washed with lysis buffer A supplemented with 10 mM imidazole. The His-tag was cleaved by human rhinovirus (HRV) 3C protease on the column for 16 hours at 4°C. The flow through fraction after the HRV 3C cleavage was purified on a gel filtration column  equilibrated with buffer A.The gene encoding 70 and Asp71 (Rho_T4L70) or Glu115 and Asn116 (Rho_T4L115) of the Rho gene. The Rho mutant with T4L attached to the C terminus (Rho_T4L426) was constructed by connecting the T4L gene downstream from the C terminus (Arg426) of the Rho gene. The Rho_T4L variants were cloned into the pET-47b vector, and the proteins were expressed and purified similarly to the wild-type Rho, except that the lysate was not heat-treated.The Rho variants with a T4L insertion (Rho_T4L70 and Rho_T4L115) were constructed by inserting the T4L gene with a two-residue spacer (Gly-Ser) on both ends between residues GlnT. thermophilus GreA was cloned into the pET-22b vector. The C-terminally His-tagged GreA was expressed in E. coli Rosetta2 (DE3). The cells were disrupted in lysis buffer B . For the EC reconstitution, 100 nM RNAP, 150 nM fluorescently labeled primer RNA , 200 nM GreA, and 100 μM NTP substrates  were added to the beads, and the mixture was incubated for 15 min at 65°C in 10 μl of M buffer. The beads were washed three times with M buffer, and the remaining EC was suspended in 4 μl of M buffer and preincubated for 1 min at 35° or 65°C for the subsequent Rho-dependent termination assay. For termination, 1 μl of a mixture of Rho  and ATP  was added to the EC on the beads. At the indicated time point, the supernatant was separated from the beads by standing the tubes for 30 s on a magnetic stand. For electrophoresis, 5 μl of urea–polyacrylamide gel electrophoresis (PAGE) sample buffer  was mixed with the sample, and the RNAs were fractionated by 10 or 15% PAGE with gels containing 7 M urea. The fluorescent-labeled RNA was imaged and quantitated with an ImageQuant LAS-4000  or Typhoon (Amersham) imager. The same reaction was performed in the absence of ATP or in the presence of ATP analogs. The ATP mimic ADP·AlF4 was prepared by mixing ADP, AlCl3, and NaF in a molar ratio of 1:5:20. The ATP mimic ADP·BeF3 was prepared by mixing ADP, BeSO4, and NaF in a molar ratio of 1:5:15.About 1 pmol of the biotinylated template DNA was captured on the streptavidin magnetic beads  in buffer A [40 mM tris-HCl (pH 7.4) and 1 M NaCl]. The DNA was digested by Pst I for 1 hour at 37°C in H buffer [50 mM tris-HCl (pH 7.5), 100 mM NaCl, 10 mM MgCl2, and 1% glycerol), and protein amounts were estimated by SDS-PAGE. Approximately 20 pmol of the EC was mixed with 25 pmol of Rho in the presence of 0.5 mM ADP·BeF3, in 400 μl of buffer C. The sample was cross-linked with 3 mM BS3 (Thermo Fisher Scientific) for 30 min at 30°C. The cross-linking was quenched by adding 100 mM tris-HCl (pH 7.5). For the grid preparation, the samples were concentrated to about 20 μl. The samples were applied to Quantifoil R1.2/1.3 Copper 300 mesh grids (Quantifoil Micro Tools) and were plunge-frozen with an EM GP2 (Leica) at 10°C and 80% humidity.The RNAP, Pst I–digested template DNA, and primer RNA were mixed at a molar ratio of 1:1.5:2 in H buffer. RNAP was walked on the template DNA by adding the ATP/UTP/CTP substrate and GreA. The mixture was incubated for 20 min at 65°C and then loaded onto a Superose 6 gel filtration column (Cytiva). Fractions containing RNAP, DNA, and full-length RNA were collected (fig. S2A); concentrated; and exchanged to buffer C [20 mM Hepes-NaOH (pH 7.5), 250 mM KCl, 5 mM MgClCryo-EM images were recorded using a Krios G4 transmission electron microscope (Thermo Fisher Scientific) equipped with a BioQuantum energy filter and a K3 direct electron detector (Gatan) (fig. S2B). Two datasets of ~13,000 and ~20,000 micrographs were collected (table S1). Movies were aligned and dose-weighted using Relion3  and subjected to 3D classification to discard particles without RNAP. The remaining ~997,000 particles were subjected to 3D refinement using an RNAP mask, followed by Bayesian polishing, local CTF estimation, and beam tilt refinement to improve the resolution. The particles from two datasets were then merged for further 3D classification, which revealed the classes of apo RNAP, EC, and RNAP-Rho complexes 1 and 2 (fig. S3). For this classification, a multitemplate reference including type 1 and type 2 complexes, EC, and apo RNAP templates, created using maps obtained from preliminary classifications, was used for better discrimination between the complexes.For the type 1 complex, the initial ~112,000 particles were refined with an overall mask and then subtracted with a mask around Rho. Several rounds of 2D and 3D classifications were performed to exclude particles with poor Rho density (fig. S4A). Approximately 43,000 particles with clear Rho density were selected for the final reconstruction of a 4.0-Å map. As the quality of the overall reconstruction was compromised by the flexibility between Rho and the EC, independent reconstructions using tight masks around EC or Rho were also performed, respectively, and used for model building (fig. S4A).For the type 2 complex, ~269,000 particles from the initial 3D classification were further classified using a mask around the type 2 complex (fig. S4B). A 5.8-Å map was reconstructed using ~147,000 particles.About 612,000 particles of EC and apo RNAP were reclassified through a 3D classification using a reference including the EC and apo RNAP templates. The selected ~220,000 EC particles and ~392,000 apo RNAP particles yielded 3.2- and 3.4-Å maps, respectively (fig. S4C).Approximately 693,000 Rho-hexamer particles were selected by 2D classification (fig. S2D) and subjected to 3D classification (fig. S3). Subsequently, ~239,000 particles were selected for 3D refinement with C6 symmetry enforced and subsequent Bayesian polishing. The particles were further 3D classified in C1 symmetry with symmetry relaxation by C6. About 205,000 particles were subjected to 3D refinement with C6 symmetry. Local CTF estimation and beam tilt refinement were performed to obtain a final 3.5-Å map.T. thermophilus Rho protomer was generated by homology modeling, using the E. coli Rho crystal structure (PDB 5JJI) (T. thermophilus EC (PDB 2O5I) (The structure model of the


RNA is spliced concomitantly with transcription and the process is organized by RNA splicing factors, transcriptional regulators, and chromatin regulators. RNA is spliced in close proximity to transcription machinery. Hence, some RNA splicing factors may play a role in transcription. Here, we show that the splicing factor SF3B2 binds to gene regulatory elements and mRNA to modulate transcription and RNA stability in head and neck squamous cell carcinoma cells. High SF3B2 expression leads to poor prognosis in patients with head and neck squamous cell carcinoma and to progression of tumor growth in mice. SF3B2 promotes tumor growth, owing to its involvement in activation of gene expression associated with mitochondrial electron transport and transcription regulatory region DNA binding. SF3B2 is enriched around the promoter element on chromatin and the transcription termination site on RNA. SF3B2 is involved in the regulation of RNA stability. According to the SF3B2-binding profile, SF3B2 regulates RNA polymerase II activity, in addition to regulating RNA splicing. Mechanistically, SF3B2 promotes the binding of structural maintenance of chromosomes 1A and CCCTC-binding factor (CTCF) to the SF3B2-binding genomic regions. SF3B2 also modulates CTCF transcriptional activity. Our findings indicate that SF3B2 has a dual function in both transcription and RNA stability, leading to head and neck squamous cell carcinoma progression.The online version contains supplementary material available at 10.1186/s13578-022-00812-8. RNA splicing is a critical step in the maturation of mRNA, for removing introns from pre-mRNA. Activities of proteins can be changed by regulating the splicing patterns of protein-coding mRNAs. Cancer cells acquire an advantage in tumor growth and resistance to anti-cancer drugs, owing to splicing variants generated by aberrant expression and mutations in RNA splicing factors . MutatioSplicing factor 3b subunit 2  is a component of the SF3b complex assembled into the U2 snRNP complex . High SFRNA splicing is coupled with elongation of transcription. The phosphorylation status of the carboxy-terminal domain of RNA polymerase II (Pol2) is critical for recruiting RNA splicing machinery . Pol2 paIn the present study, we revealed that SF3B2 regulates transcription activity of structural maintenance of chromosomes 1A (SMC1A), a cohesin component, and CTCF, in parallel with RNA splicing regulation. SF3B2 signals were enriched in gene expression regulatory regions on chromatin and near transcription termination sites on RNA. SF3B2 promoted SMC1A loading on the SF3B2-binding genomic elements and was associated with the suppression of CTCF-mediated transcription activation. High SF3B2 expression resulted in the activation of mitochondria-related gene expression. High SF3B2 expression was also associated with poor overall survival in patients with HNSCC and promoted tumor growth in mouse HNSCC xenograft model. Collectively, our findings indicate that SF3B2 has a dual function in gene regulatory elements and RNA, suggesting an SF3B2-mediated feedback loop between transcription and RNA abundance.High SF3B2 expression promotes tumor progression in CRPC by increasing the expression of androgen receptor splicing variant 7 (AR-V7) in prostate cancer . High SFTo determine how SF3B2 contributes to increasing malignancy in solid tumors aside from CRPC, we aimed to elucidate the functions of SF3B2 in HNSCC. We reanalyzed clinical data from previous studies using cBioPortal –20. Our Next we established SF3B2 stably-expressing HNSCC cells using FaDu (GFP-FaDu and GFP-SF3B2-FaDu) and Detroit562 (GFP-Detroit562 and GFP-SF3B2-Detroit562) cells , 22 FigC. High STo elucidate how SF3B2 promotes tumor proliferation in HNSCC, gene expression profiles were analyzed using RNA sequencing (RNA-seq) in SF3B2-overexpressing (GFP-SF3B2-FaDu) and SF3B2-depleted (siSF3B2-treated) FaDu cells. Gene Ontology (GO) analysis revealed that SF3B2-overexpressing cells had increased expression of genes related to mitochondrial electron transport  and recognizes the DNA motif; it was enriched at SF3B2-binding genomic regions  to determine whether SF3B2 is involved in transcription regulation   and RNA (RNA-seq) on gene and nascent transcript expression levels. SF3B2 overexpression in FaDu cells increased the expression of genes associated with SF3B2–chromatin binding (p < 2.2e−16) and decreased the expression of genes associated with SF3B2–RNA binding (p = 1.85e−08), compared to the expression levels without SF3B2 binding Fig. A. The efFOSL1, FOS, MYC, and RPS12  tag, from FaDu cells stably expressing SF3B2-TAP and EGFP-TAP (control); subsequently, the proteins were analyzed by mass spectrometry Fig. A. SF3B2 Finally, we examined gene and nascent transcript expression levels to elucidate whether SF3B2 modulates SMC1A and CTCF transcriptional activity. SF3B2 depletion did not change the nascent transcript and mRNA expression of genes associated with SMC1A- and SF3B2-binding or genes solely associated with SMC1A-binding ; in contrast, high SF3B2 expression increased the expression of genes associated with both SMC1A- and SF3B2-binding, compared to the expression level associated with only SMC1A-binding Fig. G. On theCollectively, the findings of this study revealed that SF3B2, an SF3b component involved in the U2 spliceosome, modulates transcription by recruiting SMC1A and regulating SMC1A and CTCF activities and RNA stability. This molecular mechanism could be involved in malignant progression in patients with HNSCC expressing high levels of SF3B2.FOSL1. High FRA1 expression is associated with poor prognosis in patients with oral squamous cell carcinoma (OSCC), a subtype of HNSCC ATP. Proteins covalently bound to radiolabeled RNA were collected and then separated using NuPAGE Novex 4–12% Bis-Tris gels . After the band corresponding to SF3B2-TAP was excised, the radiolabeled RNA was isolated from the RNA–protein complex using proteinase K. A 5′ linker was ligated to the isolated RNA fragments. The linker-ligated RNAs were separated using a 10% TBE-urea gel , and the bands between 70 and 130 nt in length were excised. The extracted RNAs were subjected to RT-PCR, and the resulting PCR products were separated using a 10% TBE gel (Thermo Fisher Scientific). PCR products between 140 and 190 bp in length were excised and eluted. The libraries were sequenced using the Illumina HiSeq X ten platform.PAR-CLIP was performed using a previously published protocol , with soeviously . TAP tageviously . The fraThe SF3B2-TAP-expressing HNSCC cell line was established using FaDu cells. The SF3B2-TAP complex was purified from nuclear extracts using TAP technology, as previously described . The purChIP was performed as previously described  using an6 FaDu cells using anti-SF3B2  and anti-H3  antibodies. Rabbit anti-mouse IgG  was used to enhance the signal. The cells were collected using a cell scraper.CUT&Tag was performed with CUT&Tag-IT Assay Kit  in 1.5 × 106 FaDu cells were collected and washed with ice-cold PBS. Drosophila melanogaster S2 cells (10% of the human cell number) were added to each sample as a spike-in control for normalization. The combined cells were resuspended in cold permeabilization buffer  and incubated on ice. The permeabilized cells were then pelleted, washed twice with permeabilization buffer, and resuspended in ice-cold storage buffer  at a concentration of 2 × 10e7 nuclei per 100 μL. Nuclear run-on (NRO) assays were performed using biotin-11-NTPs. In total, 2 × 10e7 nuclei per 100 μL were thoroughly mixed with an equal amount of pre-heated 2 × NRO reaction mixture  and incubated at 37 °C for 3 min in a heat block. Nascent RNA was extracted, purified, and fragmented by base hydrolysis in 0.2 N NaOH on ice for 10 min. After neutralization, fragmented nascent RNA was bound to DynabeadsTM M-280 Streptavidin magnetic beads (Invitrogen) and incubated for 20 min at 4 °C. The beads were sequentially washed as follows: twice in high-salt buffer , twice in medium salt buffer , and once in low-salt buffer . Biotinylated RNA was extracted from the beads and precipitated using ethanol. The 3′ RNA adaptors were ligated to biotinylated RNA, and the second round of biotin-streptavidin purification was performed. The mRNA cap was then removed, and the reverse 5′ RNA adaptor was ligated. After the third round of biotin-streptavidin purification, adaptor-ligated nascent RNA was reverse-transcribed into complementary DNA (cDNA) using the RP1 primer. cDNA was amplified with index primers, and amplicons of 120–350 bp were selected using AMPure XP beads . Equimolar concentrations of library fractions were pooled and sequenced using a high-output flow cell on the NovaSeq 6000 platform (Illumina).PRO-seq was performed as previously described . BrieflyThree days after 10 nM siRNA transfection to FaDu cells using Lipofectamine RNAi MAX , the cells were treated with 5 µg/ml actinomycin D for 0.5, 1, 2, and 4 h. RNA was collected using Sepasol-RNA I Super G . The amounts of target RNA were measured using iTaq Universal SYBR Green One-Step Kit  with specific primers as shown below. qRT-PCR was performed using CFX Connect Real-Time PCR Detection System (BioRad). FOSL1 F: GGCCTTGTGAACAGATCAGC and R: AGTTTGTCAGTCTCCGCCTG; MYC F: ACAGCTACGGAACTCTTGTGCGTA and R: CAGCCAAGGTTGTGAGGTTGCATT; FOS F: AGATTGCCAACCTGCTGAAGGAGA and R: TCAGATCAAGGGAAGCCACAGACA; RPS12 F: TCCGTCCTACCGGAAACCTA and R: TTCCAAACAGCAACCCACAC; 18S rRNA F: TCAACTTTCGATGGTAGTCGCCGT and R: TCCTTGGATGTGGTAGCCGTTTCT.t-test was used to compare two parametric samples, and the Tukey–Kramer test was used for comparisons between multiple parametric samples. Welch’s t-test was used to compare two non-homoscedastic samples with a normal distribution. Pairwise Wilcox rank sum test adjusted with Bonferroni correction was used for comparing multiple samples. Fisher’s exact test with Monte Carlo simulation was used for Fig. Student’s two-tailed https://www.gnu.org).awk v4.1.3 (Bedtools 2.26.0/2.29.2 Bowtie 2–2.2.3/2.3.5.1 cERMIT 1.1 Cutadapt 1.9.1 DESeq2 1.26.0 http://hannonlab.cshl.edu/fastx_toolkit/).FASTX-Toolkit 0.0.13 (https://www.bioinformatics.babraham.ac.uk/projects/fastqc/).Fastqc 0.11.5 .Perl 5.14.2 (https://www.r-project.org).R 3.6.3 (https://www.rstudio.com).Rstudio 1.4.1103 .TrimGalore 0.6.6/0.64_dev (https://anaconda.org/bioconda/ucsc-bigwigaverageoverbed).ucsc-bigWigAverageOverbed v2 (https://anaconda.org/bioconda/ucsc-wigtobigwig).ucsc-wigToBigWig v4 (https://anaconda.org/bioconda/ucsc-bedgraphtobigwig).ucsc-bedGraphToBigWig v4 (https://bioconductor.org/packages/release/bioc/html/AnnotationDbi.html).AnnotationDbi v1.48.0 (clusterProfiler v3.14.5 DOSE v3.12.0 https://cran.r-project.org/web/packages/dplyr/index.html).dplyr v1.0.4 .enrichplot v1.6.1 (http://ggplot2.org).ggplot2 v3.3.3  (http://https://bioconductor.org/packages/release/data/annotation/html/org.Hs.eg.db.html).org.Hs.eg.db v3.10.0 (plyr v1.8.6 reshape2 v1.4.4 rtracklayer (version 1.48.0) https://cran.r-project.org/web/packages/tidyr/index.html).tidyr v1.1.2  Cumulative bar chart of neoplasm histologic grade (A), HPV status (B), and alcohol consumption frequency (C). (D) Dot plot of person cigarette smoking history pack-year value. Clinical data were analyzed using cBioPortal. Figure S2. Autoradiograph of SF3B2 PAR-CLIP. 32P-labeled RNA crosslinking-SF3B2-TAP was detected by autoradiograph. Proteins were separated in SDS-PAGE and transferred to the membrane. Figure S3. RNA polymerase II activity in SF3B2 knockdown or overexpression. (A) Dot plot of correlation between replicate 1 (rep 1) and replicate 2 (rep 2) in each PRO-seq library. (B) Line plot of nascent transcript density around TTS in siSF3B2 and siControl-treated FaDu cells or GFP- and GFP-SF3B2-FaDu cells. Figure S4. Protein interaction network between SF3B2-associated proteins and DNA-binding motifs. (A) Representative protein interaction networks are shown with p value. The network of protein interaction was analyzed using Metascape. (B) FRA1 motif in SF3B2 and SMC1A overlapping peaks in GFP-FaDu cells. (C) FRA1 motif in SF3B2 and SMC1A overlapping peaks where SF3B2 overexpression increased counts of SMC1A 1.5-fold or more. (D) CTCF motif in SF3B2 and SMC1A overlapping peaks in GFP-FaDu cells. (E) Western blots of SMC1A and H3 in wild type and GFP or GFP-SF3B2 stably-expressing FaDu cells. Figure S5. Original images of western blots and silver staining.Additional file 2: Lists of genes assigned to the RPS or STRESS gene ontology.


As the basis of animal reproductive activity, normal spermatogenesis directly determines the efficiency of livestock production. An in-depth understanding of spermatogenesis will greatly facilitate animal breeding efforts and male infertility treatment. With the continuous development and application of gene editing technologies, they have become valuable tools to study the mechanism of spermatogenesis. Gene editing technologies have provided us with a better understanding of the functions and potential mechanisms of action of factors that regulate spermatogenesis. This review summarizes the applications of gene editing technologies, especially CRISPR/Cas9, in deepening our understanding of the function of spermatogenesis-related genes and disease treatment. The problems of gene editing technologies in the field of spermatogenesis research are also discussed. The world population is gradually expanding. Already, projections have been made that the world population will increase to 9–10 billion by 2050, and the future demand for cereals and animal products will increase to unprecedented levels . The rapAs a necessary part of sexual reproduction, gametogenesis is the basic guarantee for the continuation of life, reproduction and the completion of evolution. Infertility affects approximately 15% of human couples globally . EffectiGene editing technologies can already be described as one of the most important technological advances of the 21st century. Technological innovations from transcription activator-like effector nuclease (TALEN) to CRISPR/Cas9 to prime editing have greatly advanced the development of gene editing technologies and research in the field of gene editing. Although there are still biosafety and ethical issues, it must be said that the emergence of transgenic farm animals and gene-edited animal models has further improved animal production and human health ,8. AnimaSpermatogenesis is a complex biological process based on the cellular transformation of stem cells . SpermatWithin STs, there is a complex intercellular communication dialog between GCs and SCs, which together constitute the seminiferous epithelium . SCs, a The STs are surrounded by a large amount of peritubular tissue, consisting of peritubular myoid cells (PTCs), fibrocyte-like adventitial cells and collagen matrix . A largeThe defense mechanism of cutting foreign invading viral nucleic acids in clustered regularly interspaced short palindromic repeats (CRISPR) showed researchers its potential to edit genes after being first discovered in 1987 . As a reCRISPR/Cas is a technology for RNA-directed modification of target sequences by Cas proteins, consisting mainly of CRISPR clusters, leading sequences (leaders), repeating sequence regions (tracers), and a set of conserved CRISPR-associated genes (Cas genes) . In prevThe revolutionary CRISPR/Cas system, CRISPR/Cas9, was universally recognized and widely used by researchers immediately after its advent in 2013. CRISPR/Cas9 has opened the door to a large number of applications for manipulation in almost all organisms, making it easier to achieve gene deletion, insertion, and substitution . HoweverThe currently known CRISPR-Cas systems can be divided into two broad classes . One claThe hallmark protein of the type I system is Cas3. It has a nuclease and a decapping enzyme structural domain that plays an important role in degrading exogenous DNA recognized by the multi-protein-crRNA complex cascade. The hallmark protein of the type II system is Cas9. Heterologous recombination of CRISPR/Cas9 system in mammalian cells can effectively accomplish gene editing . ThroughWith the successive discovery of Cas proteins, the CRISPR/Cas system can edit DNA, but also has more functions such as editing RNA and single- and double-stranded nucleotides. This extends the editing scope of the CRISPR/Cas system while extending its applications in biomedicine, agriculture, forestry or other fields ,31. CRISWith development and upgrading, gene editing technologies have become very intuitive in helping us understand more about key genes and proteins in spermatogenesis through the easy construction of cellular or animal models. The advent of a large number of animal models, particularly mouse models, has led to a renewed understanding of the role of these genes and proteins in spermatogenesis. A significant number of genes have been found to be critical for spermatogenesis and male fertility, but many genes that we thought were associated with spermatogenesis have been shown to be dispensable.The most widely used gene editing technology in the field of spermatogenesis research is currently the CRISPR/Cas9 system. A database search revealed that more than 100 related studies have been reported since 2015, and 55 genes have been further confirmed to be relevant to male GC proliferation, sperm head and tail formation, or sperm motility .Spata16, is also known as NYD-SP12. SPATA16 was first identified and characterized as a novel testis-specific protein in 2003. Min Xu et al. found that Spata16 mRNA expression levels were 30-fold higher in human adult testes than in fetal testes, and they speculated that SPATA16 may be involved in spermatogenesis through its role in the Golgi apparatus [Spata16 is closely associated with acrosome formation and that its pathogenic mutations can cause globozoospermia and male infertility [The protein SPATA16, encoded by pparatus . Subsequertility ,91,92.Spata16 found in patients with globozoospermia, Yoshitaka Fujihara et al. successfully constructed the corresponding point mutation mouse model Spata16pm/pm by CRISPR/Cas9 [Spata16pm/pm mice. However, the sperm of Spata16−781/−781 mutant mice stalled and exhibited sterility after the deletion of 781 bp around the fourth exon of mouse Spata16 with CRISPR/Cas9. This suggests that the C-terminus of the fourth exon of Spata16 encoding the TPR structural domain is essential for male fertility. Furthermore, the Spata16 mutation produces a different phenotype in humans and mice. The same mutation causes globozoospermia in humans but spermatogenic arrest in mice. Thus, the mechanism of Spata16 in spermatogenesis requires further studies for elucidation.Based on a mutation  localized in the fourth exon of SPR/Cas9 . InteresDmrt1 plays a key role in sex determination, differentiation and development by controlling testicular development and male GC proliferation [Dmrt1 is specifically expressed in testes and is very dynamically expressed in somatic cells and GCs [Dmrt1 is linked to sex determination because of chromosome 9, where it is located. The deletion of the distal short arm of chromosome 9 was found to be associated with 46, XY gonadal hypoplasia and XY sex reversal in a large number of clinical cases [Dmrt1 deficiency is directly associated with disorders of sexual development. Subsequently, Shinseog Kim et al. identified the different functions of Dmrt1 in GCs versus supporting cells by conditional gene targeting. Their study confirmed the multiple roles of Dmrt1 in controlling the remodeling and differentiation of the juvenile testis [Dmrt1 is required for the establishment of postnatal spermatogenesis and the maintenance of the pool of progenitor cells that participate in adult spermatogenesis. In addition, Dmrt1 is involved in regulating the self-renewal of SSCs and maintaining their pluripotency [Dmrt1 function has made researchers more certain that understanding Dmrt1 will likely help enable artificial manipulation of spermatogenesis.As the first sex differentiation gene identified and the only one that is evolutionarily conserved among mammalian species, feration ,94,95. D and GCs ,97. Humaal cases ,99,100. e testis . It can ipotency ,103,104.Dmrt1 in more detail. CRISPR/Cas9-mediated Dmrt1 mutation animal models were first implemented in tilapia. A distinct phenotype was observed for the G0 generation of Dmrt1 mutant tilapia constructed by Minghui Li et al., and this phenotype was consistent with the gonadal phenotype induced by TALENs [Dmrt1 mutant zebrafish by CRISPR/Cas9 [Dmrt1 caused defective testicular development. The differentiation of GCs of all types was severely impaired, and their number was drastically reduced. GC-associated and testicular somatic-cell-associated genes were also differentially dysregulated due to Dmrt1 deletion. All these results support the hypothesis that Dmrt1 is involved in regulating testicular development and male GC proliferation. By constructing a joint study in Amh mutant zebrafish, Qiaohong Lin et al. also found that Amh and Dmrt1 synergistically maintain spermatogenesis by regulating male GC self-renewal and differentiation [Dmrt1-deficient models, such as mouse and chicken models, has allowed us to further define the critical role of Dmrt1 in sex determination and spermatogenesis [Gene editing technology has made it possible to determine the function of y TALENs . QiaohonSPR/Cas9 . The delntiation . The conogenesis .Spata16 and Pick1, Dpy19l2 is the third gene in which defects have been identified to be closely associated with globozoospermia [Dpy19l2, located in the inner nuclear membrane, actively participates in the attachment process of the acrosome to the nuclear envelope [Dpy19l2 blocks sperm head elongation and acrosome formation, leading to male infertility [Dpy19l2 further deepened the understanding of Dpy19l2 mutation-induced globozoospermia [Dpy19l2-deficient human globozoospermia and those of normozoospermia by tandem mass (TMT) quantitative proteomics analysis [Dpy19l2 induce aberrant expression of many unknown factors. There are also many mechanisms that we do not yet understand that work together to cause globozoospermia. With the discovery of FAM209, the first protein that interacts with DPY19L2, our knowledge of the in vivo mechanism of action of DPY19L2 has become even richer. Studies have confirmed that the FAM209-DPY19L2 complex maintains normal acrosome biogenesis and spermatogenesis [Similar to ospermia . Dpy19l2envelope ,109. A hertility . Afterwaospermia ,112,113.analysis . This fiogenesis . In addiogenesis ,117.Tsga10 was first identified and characterized in 2001 by M H Modarressi et al. [Tsga10 is a testis-specific expressed gene consisting of 19 exons. Modarressi et al. then found that the Tsga10-encoded sperm cell protein is processed into fibrous sheath protein in mature sperm [Tsga10 is considered to be an important regulatory gene for the formation of the fibrous sheath of the sperm tail. As research on acephalic spermatozoa syndrome continues to advance, Tsga10 has been identified as one of the candidate genes for the syndrome [Tsga10 directly cause acephalic spermatozoa syndrome [Tsga10, Geng Luo et al. constructed +/−Tsga10 mice by CRISPR/Cas9 [+/−Tsga10 mice showed disturbed mitochondrial sheath formation, significantly low sperm motility, and male sterility. This finding further defines the role of Tsga10 in spermatogenesis. Rezvan Asgari et al. further found that abnormal spermatogenesis due to the deletion of Tsga10 may be associated with autophagy [Tsga10 expression attenuated its inhibition of HIF-1, leading to diminished autophagy and the overproduction of reactive oxygen species (ROS) and resulting in impaired sperm maturation.i et al. . Tsga10 re sperm . Therefosyndrome . Loss-ofsyndrome ,122,123.SPR/Cas9 . Tsga10+utophagy . ReducedThe successful gene editing of mouse SSCs using TALEN or CRISPR/Cas9 indicates that gene editing technologies will become an important tool for studying spermatogenesis and revealing the mechanism of the development of spermatogenesis abnormalities. In addition to advancing basic research, the combination of gene editing technologies and SSC transplantation technology makes it possible to produce transgenic animals more rapidly and to better achieve the conservation of good animal breeds. However, the complexity and inefficiency of traditional gene editing technologies have limited the success rate of editing SSCs. The creation of CRISPR/Cas9 has greatly solved this problem.Crygc in mouse SSCs and successfully completed the repair and correction of genetic defects in mice [w/KitwvKit mice was subsequently corrected by Xiaoyu Li et al. via CRISPR/Cas9 in vitro [−/−Etv5 mice that were successfully constructed could adopt and support foreign SSCs and produce donor-derived sperm, the efficiency of this process was very low. The quantity and quality of sperm produced by −/−Etv5 mice were not ideal. It can thus be seen that research is still needed to further refine the protocol of SSC transplantation to construct transgenic animals. There is no denying that the application of gene editing technologies has allowed researchers to delve further into the complex and mysterious process of spermatogenesis. Gene editing technologies have also opened up new avenues of development in the medical, biomedical and agricultural fields.Yuxuan Wu et al. provided the first theoretical justification for the use of CRISPR/Cas9 to correct genetic defects in 2013 . Two yea in mice . The corin vitro . After bin vitro . AlthougAs an interdisciplinary field involving histology, embryology, molecular biology, genetics, etc., the study of spermatogenesis is one of the research hotspots in the field of reproductive biology. The regulatory roles of DNA and RNA methylation modifications, histone modifications, noncoding RNAs, exosomes, hormones, and various testicular somatic cells during spermatogenesis have been discovered in a stepwise manner ,132,133.In spermatogenesis studies, most of the existing animal models are fish or mouse knockout models, which may be due to the easier handling and lower cost of fish and mice. However, there is a lack of an accepted and complete system of phenotypic evaluation indicators for the models. Single-gene knockout animal models exploring the presence or absence of reproductive disorders have limitations for our deeper understanding of spermatogenesis. Morphologically normal sperm produced by knockout animals may also have some recessive abnormalities leading to infertility. Therefore, visual indicators such as sperm viability, sperm count, and testicular histomorphology alone can no longer meet the needs of existing research. The need for a more in-depth evaluation of animal models constructed by gene editing is urging researchers to explore the underlying causes of spermatogenesis rather than making the crude assumption that a particular gene or protein is important or unimportant.Although the use of mice as research subjects can reveal universal mechanisms in mammals, these studies are still at a stage where they can provide only a theoretical basis for practical animal breeding work. At this point in time, very little research has been carried out on livestock and poultry. This fact suggests that the mechanisms of spermatogenesis are not as clear-cut as we thought and that there are still many problems that need to be solved in the practical application of gene editing technology in production. Therefore, more research in livestock and poultry is needed in the future. A comprehensive and systematic analysis of the mechanisms underlying the various biological processes involved in spermatogenesis will facilitate the development of animal breeding, as well as developmental and reproductive biology.In addition, the combination of gene editing and SSC transplantation offers new ideas for the treatment of male infertility, but further research is needed to establish the optimum transplantation process . However


Despite the widespread use of the single item self-rated health (SRH) question, its reliability has never been evaluated in Chinese population.n = 11,429). Kappa (κ), weighted kappa . In wave 1, the same SRH question was asked twice, separated by other questions, on a subset of 4533 subjects, allowing us to examine the test–retest reliability of SRH. In addition, two versions of SRH questions (the WHO and US versions) were asked (ρ > 0.8). Compared with excellent/very good SRH, adjusted hazard ratios (HR) of death are 2.30  for the US version and 1.86  for the WHO version. Using slope indices of inequality, the WHO version estimated slightly larger mortality differences  than the US version .There was moderate to substantial test–retest reliability (κ = 0.54, In Chinese middle-aged and older population, the reliability of SRH is generally good, although the two commonly used versions of SRH scales could not be compared directly. Both indices predict mortality, with similar predictive validity.The online version contains supplementary material available at 10.1186/s12889-022-14218-1. The single item self-rated health (SRH) has been widely seen as an indicator of overall health status. SRH has been shown to be an independent predictor of morbidity and mortality –7. ThereSRH is usually measured by asking individuals to evaluate their health on a five-point scale (could be more or less categories) with or without a given reference point (self-comparative or age-comparative) , 11. TheMoreover, previous studies have shown that the predictive validity of mortality of SRH may differ between populations and certain subgroups , 16, andP < 0.01), but not among women [The validity of SRH refers to the accuracy of the measure, while the reliability of SRH refers to the consistency and stability of the measure. The evidence on the reliability of SRH among adults is limited. We found only 4 studies on reliability of SRH in adults –22, and ng women . Howeverng women . Furtherng women , 22. A sTo our knowledge, none of previous studies compared the two commonly used versions of five-point scale of SRH in Asian population, and none of the previous studies evaluated the reliability of SRH scales in Chinese population. To fill those gaps, the current study compared the two versions of SRH and assessed the reliability of SRH among nationally representative sample of Chinese residents. In addition, the current study also assessed the predictive validity of mortality of the two SRH scales among Chinese middle-aged and older population.This study used data from China Health and Retirement Longitudinal Study (CHARLS) , which iTwo versions of the five-point scale of SRH were used to measure general health status in CHARLS wave 1 (2011), wave 2 (2013), and wave 3 (2015). In the face-to-face interview, respondents were asked with questions “Would you say your health is excellent, very good, good, fair, or poor?” and “Would you say your health is very good, good, fair, poor, or very poor?”. Every respondent was asked to rate their health status twice, once at the beginning of the Health Status and Functioning Section and again at the end of that section . Order of the two questions was randomly assigned. However, the design of the SRH measurement in CHARLS wave 1 is special.Among 17,708 CHARLS wave1 respondents, 15,962 individuals rated their general health status using both or one of the two SRH scales at the beginning and the end of the Health Status and Functioning Section. We divided the respondents into three groups according to their responses to the two SRH scales. Group 1 used scale 1 at the beginning of the Health Status and Functioning Section and scale 2 at the end of that section. Group 2 used scale 2 at the beginning of the Health Status and Functioning Section and scale 1 at the end. Group 3 used scale 2 twice, once at the beginning of the Health Status and Functioning Section and again at the end. This special design provided an opportunity to study the reliability of SRH in terms of (1) the test–retest reliability of the same SRH scale measured by scale 2; (2) the effect of different SRH scale versions; (3) the effect of SRH question orders; (4) and the effect of other health-related questions between two SRH measurements.The analytical sample was defined as respondents aged 45 years or older, including both main respondents and age-eligible spouses, who reported SRH both at the beginning and the end of the Health Status and Functioning Section without the use of any proxy. Sample selection procedure was shown in Fig. First, we examined the distribution of SRH responses according to the order of questions and cross-tabulated the distribution of SRH responses to scale1 and scale 2 when combined group 1 with group 2. Second, to test the reliability of SRH, we used four measurements: (1) Proportion of agreement  , 29. Kapy chance ; (4) andment}κw) . Weightey chance . Weight To assess the effect of SRH version, we compared responses to scale1 and scale 2 in group 1, group 2, and in combined sample (group 1 and group 2), separately. The first two comparisons also reflect the effect of question orders and the effect of other health-related questions between two SRH questions.To assess test–retest (intra-rater) reliability, we compared the SRH measured at the beginning and at the end of the Health Status and Functioning Section among group 3 respondents. For this comparison, we used three-category SRH and five-point scale SRH, separately. In addition, we assessed the test–retest (intra-rater) reliability of SRH  according to sample characteristics including age, sex, area type, education, chronic disease history, and major accidental injuries.n = 190) with missing data in covariates were analysed as a separate category. Interaction terms between SRH and each independent variable were used to identify potential effect modification. Likelihood ratio test (LRT) was used to assess whether the model fit was improved. Six regression models were presented in the results.To assess the predictive validity of mortality of SRH, Cox proportional-hazards models were estimated, and hazard rate ratio (HR) and 95% confidence interval (CI) were calculated. The associations between SRH measured by scale 1 and scale 2 with all-cause mortality were assessed among group 1 and group 2 respondents. Proportional hazards assumption was tested based on Schoenfeld residuals. Covariates including age, sex, area type, education, chronic diseases, and major accidental injuries were added to the model consecutively. The few respondents  and slope index of inequality (SII) by two five-point SRH scales were estimated to measure the magnitude of inequalities in mortality rate (MR). We estimated RII  to indicate relative inequality and SII  to indicate absolute inequality. RII was estimated with age- and sex- adjusted Poisson regression model. It was the ratio of the mortality of people with the worst SRH (x = 1) to the best SRH (x = 0). SII was calculated by the following formula: /(RII+1) . Large s/(RII+1) .CHARLS adopted a stratified multi-stage probabilities proportional to size (PPS) random sampling strategy . To accoTable Distribution of responses to scale 2 is more balanced than that of scale 1. Proportions of “very good” and “very poor” are similar in scale 2, while there are 27.5% and 17.5% differences between “excellent” and “poor” options in scale 1. “Fair” category took the largest proportion. Nearly half of the respondents chose “fair” on all four occasions. In general, health (in terms of the meaning of the word) measured by scale 1 is better than it measured by scale 2. On the second inquiry, 32.7% of respondents chose positive answers and 18.6% chose negative answers when using scale 1, while only 23.4% of respondents chose positive answers and 25.5% chose negative answers when using scale 2. The stratified results of Table n = 7,448) of respondents choose categories with the same meaning and 19.3%  choose the one in the same position. Results adjusted for baseline weights can be found in supplementary data table ATable n = 3,125) of respondents chose the same category and 31.1%  changed their ratings after answering questions on disease history, lifestyle, and health behaviours. Results adjusted for baseline weights can be found in supplementary data table ATable  n = 1,40 changed Reliability statistics was presented in Table In terms of the test–retest reliability of SRH , agreement is higher when SRH was categorized into three categories  and 0.42  in the global test indicated the assumption was met.Table The association between SRH measured by scale 1 and all-cause mortality is shown in Table Association between SRH measured by scale 2 and mortality is also shown in Table P = 0.08 and 0.06, respectively), however, according to the results of LRT, including the interaction terms improve the prediction . Results adjusted for baseline weights can be found in supplementary data table AFor both SRH measured by scale 1 and scale 2, age is an important confounder in the association between SRH and all-cause mortality. The association attenuated substantially after adjusting for age (attenuation > 10%). However, additional adjustment of sex increased the effect of this association. There is weak evidence for interactions between education and SRH measured by the two scales  . The stuκw=0.58) , and didThe study on SRH and mortality from Hong Kong used three-category age-comparative SRH and self-comparative SRH to measure health status among respondents aged 65 or over living in Elderly Health Centres in Hong Kong . It repoJürges and colleagues compared the WHO version  and US version scale 1) of SRH using data from the Survey of Health, Ageing and Retirement in Europe (SHARE) . Consist of SRH uAnother study using data from the English Longitudinal Study of Ageing (ELSA) assessed the effect of question order and response-choices of SRH . ConsistThere are several limitations of this study. First, the reliability assessment was based on cross-sectional data. Therefore, we could not take account of the effect of longer time period. Second, the predictive validity of SRH was assessed only in terms of all-cause mortality, which, although being representative, could not show the potential differences between specific health outcomes. Third, as the SRH information was only from baseline wave, we could not assess the change in the predictive validity of SRH overtime. However, one previous study reported that the predictive validity of mortality of SRH is increasing over time .Our study suggests measurement error in SRH among Chinese middle-aged and older adults. Responses to SRH questions depend on the version of the scale, question order, sample characteristics such as age, education, area type, and whether experienced major accidental injuries. Researchers should consider the effect of the above factors when designing studies or interpreting their results. Both SRH versions predict all-cause mortality among Chinese middle-aged and older adults, however, given the difference in categories between the two scales, the effect estimates appear to differ, although the RII and SII were similar. In addition, the WHO version and US version SRH are both effective in measuring health status, but they could not be compared directly. When using SRH to measure health status, Chinese population tend to report worse health than Western population, therefore, the results need to be interpreted cautiously.This study for the first time assessed the reliability of SRH among Chinese population. Overall, there was moderate to substantial test–retest reliability of SRH in Chinese middle-aged and older adults, and the reliability was higher in some subgroups. Both SRH versions can predict mortality among Chinese middle-aged and older adults, with similar predictive validity. Although the two SRH versions measured the same latent variable, they could not be compared directly among Chinese middle-aged and older population.Additional file 1: Table A1.  Weight used in the calculation of weighted kappa. Table A2.  Distribution of self-rated health responses according to the order of questions stratified by groups. Table A3.  Distribution of self-rated health responses according to the order of questions after adjusting for baseline weights. Table A4. Cross-tabulation of self-rated health measured by scale 1 and scale 2 after adjusting for baseline weights. Table A5.  Cross-tabulation of self-rated health measured at two occasions after adjusting for baseline weights. Table A6.  Cross-tabulation of self-rated health responses at two occasions among group 1 and group 2 respondents (n=11429). Table A7.  Cross-tabulation of three-point scale 1 and scale 2 responses among group 1 respondents (n=7898). Table A8.  Cross-tabulation of three-point scale 1 and scale 2 responses among group 2 respondents (n=3531). Table A9.  Cross-tabulation of three-point scale 1 and scale 2 responses among group 1 and group 2 respondents (n=11429). Table A10.  Cross tabulation of three-point scale 2 responses among group  3 respondents (n=4533). Table A11.  Distribution of self-rated health responses among group 1 respondents (n=7898). Table A12.  Distribution of self-rated health responses among group 2 respondents (n=3531). Table A13.  Reliability of self-rated health after adjusting for baseline weights. Table A14. Test-retest reliability of self-rated health according to sample characteristics after adjusting for baseline weights. Table A15. Hazard rate ratio of death (HR), mortality rates per 1,000 person-years (MR), relative index of inequality (RII) and slope index of inequality (SII) among Chinese middle-aged and older adults (n=11429) (Results adjusted for baseline weights). Table A16. Self-rated health and age-adjusted hazard rate ratio of death (HR) stratified by education.


In addition to such “demographic restoration” efforts, manipulating the thermal tolerance of outplanted colonies through assisted relocation, selective breeding, or genetic engineering is being considered for enhancing rates of evolutionary adaptation to warming. Although research into such “assisted evolution” strategies has been growing, their expected performance remains unclear. We evaluated the potential outcomes of demographic restoration and assisted evolution in climate change scenarios using an eco‐evolutionary simulation model. We found that supplementing reefs with pre‐existing genotypes (demographic restoration) offers little climate resilience benefits unless input levels are large and maintained for centuries. Supplementation with thermally resistant colonies was successful at improving coral cover at lower input levels, but only if maintained for at least a century. Overall, we found that, although demographic restoration and assisted evolution have the potential to improve long‐term coral cover, both approaches had a limited impact in preventing severe declines under climate change scenarios. Conversely, with sufficient natural genetic variance and time, corals could readily adapt to warming temperatures, suggesting that restoration approaches focused on building genetic variance may outperform those based solely on introducing heat‐tolerant genotypes.Interest is growing in developing conservation strategies to restore and maintain coral reef ecosystems in the face of mounting anthropogenic stressors, particularly climate warming and associated mass bleaching events. One such approach is to propagate coral colonies  Coral reefs worldwide are threatened by a variety of local and global stressors, causing widespread declines in these important ecosystems  and immigration, which was the product of the larval input rate (la) and the amount of free space at that patch (Fa). Each coral subpopulation at a given reef patch had an optimal growing temperature za that could evolve over time through gene flow and selection. Evolutionary dynamics of the optimal growing temperature were specified as:where zi,a is the population‐weighted mean trait value of larvae immigrating into patch a, V is the additive genetic variance and qa reduced the strength of natural selection at very low coral cover.where V) provided the raw material for evolution  relative to the current trait value za at that reef, as well as the larval input rate (la) and the amount of free space (Fa). Free space was defined as the habitat area that was not occupied by coral or macroalgae:V) and the fitness of a given trait value, with an additional term, qa, which reduced selection at vanishingly low population sizes  of each coral subpopulation was determined by its growth  and mortality  rates, and interspecific competition that was encoded in an interaction matrix (α) where αCM was the effect of macroalgae (M) on coral (C) and αCC was the effect of coral on itself:Ma is the percent area at reef patch a occupied by macroalgae. To test the sensitivity of the model to underlying assumptions of reef bistability  and mortality  of corals were specified as Gaussian and exponential functions, respectively, of local temperature (Ta) relative to a population's current optimal growing temperature za:rC,0 is a coral growth scaling factor, and w is the width of coral thermal tolerance. Following Walsworth et al. (Ta>za).Growth  experienced a settlement rate of 0. Larval input, la, was calculated from the connectivity matrix D in which Dab was the probability of larvae from patch b reaching patch a, and the effective fecundity rate β:Simulating outplanting”); all of these connections were of equal strength (Dab=0.2) and all patches were assumed to be equal in size.Both population and evolutionary dynamics were influenced by dispersal among coral subpopulations. Following McManus et al. (2021), our model specified spatially explicit dispersal where larval settlement into a given patch increased with free habitat area, and a reef without free habitat area  where the incoming trait values were calculated as:zb is the average trait value of corals at patch b.In addition to affecting population dynamics, larval exchange among subpopulations or patches also contributed to the evolution of thermal optima across the reef network. Gene flow arising from dispersal was determined by the population‐weighted trait value of incoming larvae (Cmin = 10−6), the strength of directional selection was reduced through qa  and mortality rates  that were independent of temperature and set as constants. As such, instead of Equation  and replenished the fractional cover to the specified amount (Ca=s) at every time step. As such, when there were n number of reefs targeted for restoration, there were a total of (20 + n) × (20 + n) elements in the connectivity matrix D. Outplanting of corals from the nurseries to target reefs was controlled by the connectivity matrix such that, Das was either 1 or 0 depending on whether reef a was or was not the focal restoration site associated with that nursery reef, respectively. The larval input rate at each patch therefore includes recruitment from four neighboring patches, self‐recruitment, and input from the nursery reef, if applicable .In addition to the metacommunity with 20 reef patches, we simulated one nursery reef, n Figure . At eachEquation . If a waClimate change was simulated as an asymptotically increasing temperature trend from a network‐wide average temperature of 27–32°C over ~200 years Figure . The magStochastic simulations were initiated for a “burn‐in” period of 1000 years in which the temperature remained stable but with annual anomalies. Fifty stochastic iterations were executed for each unique set of parameter combinations that we explored. Simulations began with corals occupying 25% of available habitat area at each reef patch with optimal growing temperatures that matched the average local temperature of their patch. Temperature increases began at the end of the burn‐in period, and the network dynamics were monitored for an additional 500 years.V) and effective fecundity (β). No supplementation occurred in these scenarios, and we explored finer scale gradients of V and β. Variation in β represents an exploration of the overall larval immigration rate, which is equivalent to varying levels of Dab.We first explored how the vulnerability of corals to climate change varied across a range of values for genetic variance (Ca=s) of 0, 0.0000001 (1 × 10−7), 0.000001 (1 × 10−6), 0.00001 (1 × 10−5) and 0.0001 (1 × 10−4) target reef area year−1. Previous studies have indicated average reef area in the order of ~100 km2 in some regions  was specified as 0, 1, 2, or 3°C greater than the target reef patch's current mean trait value. Because the optimal growing temperature of a given subpopulation could evolve over time, Za=s was re‐defined each year based on that reef's current trait value.We then simulated various forms of demographic restoration and assisted evolution concurrent with climate change across the 500‐year monitoring period. We explored supplementation levels  was targeted for supplementation. We explored three possible spatial designs which targeted patches for restoration based on their temperature regime. The “hot strategy” focused restoration effort on the four hottest reefs Figure , represeV) ranging from no genetic variance (V=0) to low genetic variance (V=0.05) and moderate genetic variance (V = 0.1). We considered parameterizations of the competition matrix that produced either coexistence of corals and macroalgae or that produced alternative stable states , corals went extinct across the reef network in response to climate warming at all levels of effective fecundity (β) when supplementation did not occur , corals at all patch types persisted, declining modestly between 50 and 250 years after warming began and then recovering to high levels of coral cover (>90%) by the end of the simulation , higher effective fecundity (β = 0.08–0.1) more effectively maintained coral cover at the coldest patches , increasing larval production exacerbated interim declines in coral cover during climate change trajectories by impeding adaptation in the hot patches  differed depending on the levels of genetic variance assumed. At low levels of genetic variance , except at the highest annual input levels considered (βCa=s = 0.0001 year−1)  also did not improve coral cover when annual supplementation was less than 0.000001 year−1 of target reef area (<0.01 ha year−1 assuming a 100 km2 reef)  in outplanted colonies lead to substantial improvements in final coral cover  under parameterizations of the competition matrix associated with coexistence of corals and macroalgae rather than alternative stable states  Figure . Assiste) Figure . ConversAppendix . AlthougAppendix . Even inAppendix . HoweverAppendix .V=0) or low (V=0.05) (Appendix V=0.1), coral cover exceeded 90% by the end of climate change projections across all scenarios explored, and supplementation or assisted evolution produced no discernible benefits  or no (V = 0) genetic variance, even with high levels of supplementation and trait enhancement  for the cold strategy, 0.29 to 0.38 for the hot strategy, and 0.17 to 0.52 for the random strategy  or selected a wide range of sites (random patches) performed comparably with one another and outperformed strategies that targeted thermal refugia (cold patches) Figure . For supy Figure , the beny Figure . ImportaV = 0.1). In simulations in which supplementation did occur, it offered little benefit for coral reefs faced with climate warming unless the thermal tolerance of outplanted colonies was also enhanced (i.e. demographic restoration had little benefit). This result is not necessarily surprising; when a population is maladapted to a changing environment and experiencing high mortality, any equally maladapted individuals added to the population will presumably die as well. In some cases, adding such genetically maladapted individuals could be deleterious and delay evolutionary rescue  as well as introducing heat‐tolerant genotypes (assisted evolution). In most model scenarios without supplementation, corals subjected to climate warming were extirpated unless existing genetic variance was sufficiently high  at a rate of 0.000001 year−1 would equate to adding roughly 6.89 ha year−1 of thermally enhanced corals to the Great Barrier Reef, (http://www.gbrmpa.gov.au), 0.04 ha year−1 for Hawai‘i's Maro Reef (https://www.papahanaumokuakea.gov) and 0.02 ha year−1 for the Belize Barrier Reef Reserve System (https://whc.unesco.org/en/list/764/). To sustain these efforts over 100–200 years would amount to a total effort of 689–1378 ha for the Great Barrier Reef, 4–8 ha for Maro reef, and 2–4 ha for the Belize Barrier Reef Reserve System. In contrast, reviews of documented propagate‐and‐transplant restoration efforts have indicated a much smaller median spatial extent of 0.01–0.02 ha sustained for only 1 year  would cost in the order of US$240 M per year, roughly 4% of the economic contribution of the Great Barrier Reef to the Australian economy . For smaller reefs (e.g. atolls) the necessary input thresholds are naturally more achievable. For instance, a 20 km2, reef would only require 0.0004 ha year−1 of thermally enhanced corals . These estimates are purely illustrative because they assume that the entire reported spatial extent for a given reef system is composed of a viable coral habitat that could be targeted for supplementation. Additionally, these costs and effort calculations do not account for outplanting mortality or additional expenses that may be associated with assisted evolution beyond those of demographic restoration  reduced the input levels necessary to achieve long‐term benefits. However, even the highest levels of assisted evolution that we considered generally failed to prevent severe and protracted reductions in coral cover during simulated climate change. Although assisted evolution facilitated the recovery of corals after these interim declines in some cases, such benefits were usually only achieved at supplementation rates of at least 0.000001 yearWith regard to spatial designs for assisted evolution efforts, we found a comparable performance between approaches that targeted the warmest, most thermally vulnerable subpopulations (hot strategy) and those focused on a portfolio of patches (random strategy). Targeting thermal refugia (cold strategy) performed relatively poorly, similar to results for conservation strategies using marine protected areas  due to the scaling of inputs by the amount of free space on target reefs (Fa), which was often limited due to proliferation of macroalgae  corals could successfully adapt to warming and persist at high levels. Although empirical estimates of genetic variance underlying thermal tolerance in corals are scarce, there is evidence to suggest that the range considered in this study, as well as higher values, are plausible  of this trait as 0.5 for A. hyacinthus, although Dziedzic et al.  than those considered in this study. Quigley et al. (Although we tested different combinations of parameter values to assess the robustness of our simulation results Appendix –S16, it y et al.  reached Although we found that assisted evolution could be beneficial when maintained at sufficiently high levels, inputs typical of existing restoration efforts failed to produce ecologically significant benefits in our simulations (Bayraktarov et al., We found that in scenarios in which corals had sufficient genetic variance to keep pace with climate change, coral cover declined only modestly as the climate warmed, and recovered faster than could be achieved through supplementation and assisted evolution. As such, our results suggest that assisted evolution efforts cannot offer comparable benefits with the presence of robust adaptive capacity. This finding lends support to the restoration framework put forth by Baums et al. , which pThe authors declare no conflict of interest.Appendix S1Click here for additional data file.