Danio rerio) model. Approximately 3,315 ERV-like elements (DrERVs) were identified as Gypsy, Copia, Bel, and class I−III groups. DrERVs accounted for approximately 2.3% of zebrafish genome and were distributed in all 25 chromosomes, with a remarkable bias on chromosome 4. Gypsy and class I are the two most abundant groups with earlier insertion times. The vast majority of the DrERVs have varied structural defects. A total of 509 gag and 71 env genes with coding potentials were detected. The env-coding elements were well-characterized and classified into four subgroups. A ERV-E4.8.43-DanRer element shows high similarity with HERV9NC-int in humans and analogous sequences were detected in species spanning from fish to mammals. RNA-seq data showed that hundreds of DrERVs were expressed in embryos and tissues under physiological conditions, and most of them exhibited stage and tissue specificity. Additionally, 421 DrERVs showed strong responsiveness to virus infection. A unique group of DrERVs with immune-relevant genes, such as fga, ddx41, ftr35, igl1c3, and tbk1, instead of intrinsic viral genes were identified. These DrERVs are regulated by transcriptional factors binding at the long terminal repeats. This study provided a survey of the composition, phylogeny, and potential functions of ERVs in a fish model, which benefits the understanding of the evolutionary history of ERVs from fish to mammals.Endogenous retroviruses (ERVs) occupy a substantial fraction of mammalian genomes. However, whether ERVs extensively exist in ancient vertebrates remains unexplored. Here, we performed a genome-wide characterization of ERVs in a zebrafish (IMPORTANCE Endogenous retroviruses (ERVs) are relics of past infection that constitute up to 8% of the human genome. Understanding the genetic evolution of the ERV family and the interplay of ERVs and encoded RNAs and proteins with host function has become a new frontier in biology. Fish, as the most primitive vertebrate host for retroviruses, is an indispensable integral part for such investigations. In the present study, we report the genome-wide characterization of ERVs in zebrafish, an attractive model organism of ancient vertebrates from multiple perspectives, including composition, genomic organization, chromosome distribution, classification, phylogeny, insertion time, characterization of gag and env genes, and expression profiles in embryos and tissues. The result helps uncover the evolutionarily conserved and fish-specific ERVs, as well as the immune-relevant ERVs in response to virus infection. This study demonstrates the previously unrecognized abundance, diversification, and extensive activity of ERVs at the early stage of ERV evolution. ERVs aroviruses .Although most of the ancient ERVs or elements in human and mouse genomes are defective and do not result in the generation of infectious viruses, hundreds of copies of nondefective ERVs were found to produce functional proteins or non-coding RNAs, which play crucial roles in normal physiologic processes , 10. In 11–16–21–gag, pol, and env genes and remains transcriptionally active. ZFERV expression is high in larval and adult zebrafish thymus and minimal in 2 days postfertilization (dpf) embryos  is a well-established experimental organism for modeling various aspects of physiology and development, given its convenient genetic and embryo manipulation, and fast embryonic growth with typical developmental periods, including zygote, cleavage, blastula, gastrula, segmentation, pharyngula, and hatching stages , which means that all the gag, pol, and env genes are lost in this case. Elements with LTRs on both ends account for 83.3% in total and 46.8% when LTR–LTR type is excluded. These outcomes showed the prevalence of DrERVs with both LTRs in the genome. Among the DrERVs with recognizable remains of protein-coding genes (PCGs), the LTR–pol–LTR accounted for 15.1%. In fact, pol is the most detected PCG; hence, the pol portions of DrERVs are retained more frequently than gag and env portions. The lengths of 5′-LTR and 3′-LTR are comparable and most concentrated in approximately 500 bp  and 2,000 to 3,000 bp (for pol). The distribution of LTRs and gag, env, and pol genes on positive and negative strands shows no remarkable bias. The number of DrERVs showed an overall high correlation with the length  and GC content  of zebrafish chromosomes. The correlation between DrERV abundance and GC content could be associated with high epigenetic modification in DrERV sequences as observed in other species  of DrERVs distributed on the whole genomes  regions of pol genes were applied for DrERVs classification as described in many other ERV researches (40–DrERVs containing predictable RT region was constructed (DrERVs were identified to be Gypsy (830), Bel (41), Copia (6), class I ERV (44), class II ERV (11), and class III ERV (9) (Table S2). Gypsy, Bel, and Copia are sometimes classified as retrotransposon elements, a proposed ancestor of retrovirus that had not acquired the env gene during evolution. However, these elements are also considered ERV-like elements in many investigations, because the env gene is occasionally found in Gypsy, and infectious Gypsy has been reported (–DrERVs. Gypsy occupies the largest proportion of DrERVs and includes three main subgroups (Gypsy1-3) with high divergences. In comparison, Copia and Bel are more convergent compared with Gypsy. Four DrERVs related to Snake-head retrovirus (SnRV) were classified to class III DrERV, this group is sometimes classified as a separate type , Walleye dermal sarcoma virus (WDSV), Salmon swim bladder sarcoma virus (SSSV) and SnRV. WEHV, WDSV, and SSSV belong to epsilonretrovirus, which indicating that epsilonretrovirus is prominent in both exogenous and endogenous retroviruses in fish. All 11 class II DrERVs were clustered with the lentivirus group, and none was clustered with alpha-, beta-, or deltaretroviruses.Given that the concatenated sequences of searches , 40–43. structed . These Dss I ERV , class Ieported –. Therefoate type , 47. As trovirus . Only foDrERVs in the genome are structurally incomplete; thus, over 2,000 DrERVs that lack the RT region were not classified by this method. Although gag and env genes are usually not used as phylogenetic markers, we applied the relatively conserved retrotrans_gag domain of gag and the TLV_coat (HR1–HR2) of env to further explore the phylogeny of DrERVs. Considering that gag and env are evolutionarily not conserved, the DrERVs classified by RT region but not exogenous retroviral sequences were used as references in classification. A total of 454 retrotrans_gag domains were identified from 1,119 gag genes and form seven subclades. Beyond our expectation, all these 454 elements were related to Gypsy . The env tree shows that all the 71 elements with TLV_coat (HR1 to HR2) domains are related to class I . Among which, DrEnv1 and DrEnv4 show high degrees of homogeneity, and the elements in these two groups seem to be copies from the same ancestor. By contrast, DrEnv2 and DrEnv3 show heterogeneity and seem to be correlated with XRVs and mammalian ERVs.Most of the to Gypsy , except  class I ; 51 addiDrERVs, by which a neutral evolutionary rate of 1.46 × 10−8 in fish was used  of the DrERVs examined possess identical LTRs at both ends. The high proportion of identical LTRs indicates that these elements could be inserted recently or under a strong positive selection pressure. In addition, some DrERVs might still keep their transposition activity. Overall, the integration times are highly concentrated in 0–1 Mya, with a proportion of 68.54% (610/890) of the DrERVs. The result implies a recent explosive integration wave in zebrafish. For other intervals, integration waves are observed at about 7 Mya, 9 Mya, 15 Mya, and 17 to 23 Mya . In addition, we found that the DrERVs with 100 to 200 bp LTR are much older than others  than other types . Gypsy1 possess the highest median insertion time (0.67 Mya) in Gypsy1 to 3; whereas Gypsy2 takes the longest time frame, which possesses the oldest DrERV (42.43 Mya) in this research ; whereas the oldest DrERV (6.68 Mya) in class I–III belongs to class I. The earlier insertion times of Gypsy and class I DrERVs may have caused the abundance of these two groups.Identical 5′-LTR and 3′-LTR are believed to start mutating separately at the very beginning of the insertion of retroviruses into host genomes. In this case, the divergence of LTRs at both ends of ERVs are usually used to make a rough estimation of the insertion time. Thus, this method was applied here to reveal the age of was used . A totaln others . The medresearch . In clasgag- and env-derived genes from humans and other species are involved in various diseases, immune responses, and other physiological processes , paraneoplastic Ma antigens (PNMA), and zinc finger protein (Znf) domains were observed at these loci. Among the 1119 gag genes, 97 SCAN, 71 PNMA, and 45 Znf domain–encoding sequences were predicted. Interestingly, the predicted domain proteins were all part of or related with zinc finger protein; SCAN and PNMA domains have been proposed to be derived from gag , we annotated five potential gag domains (assigned as DrGD) by sequence comparison . In the phylogenetic tree, class I gag has two main branches, and gag from class II DrERVs formed an independent clade; however, four class III gag formed a mixed clade with some class I gag genes, which could be a result of recombination or transposition ; only Ovine progressive pneumonia virus (OPPV) and SnRV retrovirus clustered with the mixed clade of class III/class I DrERVs. We found that DrGD1 is the most representative domain in DrERVs and kept by all the eight XRVs and ERVs. All the four viruses and two ERVs in the main virus group belong to class I, which comprise two epsilonretroviruses, namely, WEHV-1 and WDSV, and four gammaretroviruses. The epsilonretroviruses possess only DrGD1, but the gammaretroviruses also hold DrGD2, which is a domain found only in the branches of class I gag. Although endogenous gammaretrovirus was not identified in zebrafish, this finding suggests that a number of gag genes in class I DrERVs have a close relationship with gammaretroviruses. By contrast, the epsilonretroviruses may have experienced a loss of DrGD2 during evolution. Both OPPV and SnRV belong to class III retrovirus, only DrGD1 was found in these two retrovirus and the clustered class III and class I gag. The solo DrGD1 in class III could be a result of the loss of other domains. DrGD3 is a unique domain of class II, DrGD4 and DrGD5 are representative in the top and bottom branches of class III gag. These results suggest that the evolution of gag is accompanied by obvious domain changes, the zebrafish gag genes may be the ancient type that retains more ancestral characteristics. Five domains may be used as markers to identify fish-derived ERVs, especially DrGD1 and DrGD2. Notably, DrGD1 and DrGD2 are retained in XRVs and mammalian ERVs.Given that multiple endogenous rocesses –52, we nfrom gag , 54. We position . Most XRenv genes were classified into four groups , ERV-S3.7.27-DanRer (classified to class III), and ERV-E3.1.25-DanRer (classified to Gypsy). Considering the close phylogenetic relationship between DrEnv3 and DrEnv4, as well as the classification of ERV-E24.2.36-DanRer, we propose that the exception of ERV-S3.7.27-DanRer and ERV-E3.1.25-DanRer env genes comes from the transposition of RT region or env genes; therefore, we tend to classify DrEnv4 to class I DrERV as well. The env genes in each branch show high sequence similarity. The insertions, deletions, or nonsynonymous mutations are found at various positions in most of the env genes. However, none was found to interrupt the putative short ORFs containing the 17 aa immunosuppressive domain (ISD) in DrEnv1–4, and some premature stop codons were found right after the ISDs of DrEnv4. In addition, the ISD sequences show high consistency in each branch but high heterogeneity across branches −transmembrane domain (TM) interaction in the ERVs of other species. However, none was found in the other three DrEnv groups. The SU and TM domains of mammalian Env proteins are cleaved by a furin cleavage site with a consensus motif of R/K-X-R/K-R. This motif-encoding sequence was also found in zebrafish DrEnv1, DrEnv3, and DrEnv4 groups, except for DrEnv2. The ISD was found in all the four groups, followed by a conserved C-X7-CC motif in DrEnv1 and a C-X6-CC motif in DrEnv2 and DrEnv3. However, this C-X5/6/7-CC motif is absent in DrEnv4. The transmembrane region is located at the C-terminus of DrEnv1–3 but lost in DrEnv4. In conclusion, DrEnv4 lost most motifs, but all the eight env genes in DrEnv3 kept all the coding potential for conserved motifs. The relative position of the motif-encoding sequences in all groups are consistent with env genes identified in other species  analysis and identified some full-length group members, including an env-encoding DrERV on chromosome 5 (ERV-E5.1.38-DanRer), which is a member of DrEnv3. Similar to HERV and other retroviruses, the transcription of ERV-E5.1.38-DanRer starts from the 5′ end of the R region in 5′-LTR and ends at the 3′ end of the R region in 3′-LTR  in the human genome are generated by the queries of DrERVs from zebrafish chromosome 4  is located in the intron-4 of Ras and Rab interactor 3 (RIN3) of human and chimpanzee, which shows a high similarity with ERV-E19.1.80-DanRer-env in a reverse direction . The target sequence has a coding potential of a 666 aa protein. The putative TM domain of this protein is substantially more conserved than the SU domain. The TM and SU domains have a genetic distance of 0.8 and 1.2, respectively. Through further analysis, we identified a previously unrecognized HERV element (HERV-14q32.12) at this position . HERV-14q32.12 contains gag, pol, and env genes and LTRs at both ends. A conserved Gag_p30 domain, a Rve domain, and a TLV_coat encoding sequence were predicted in the gag, pol and env gene, respectively; however, the usually more conserved RT domain encoding sequence was absent, and gag and pol were truncated with premature stop codons. The 147 retrotrans_gag domain-containing gag genes generate only three nonredundant hits, namely, Retrotransposon Gag-like 1 and 5 and Paternally expressed 10. The gag genes that lack retrotrans_gag domain were also used to search the human genome. These elements generate more hits with more substantial E-value, among which ERV-AB4.6.45-DanRer-gag and HERVE-int-19p12-gag showed highest similarity  .In addition, the DrERVs in zebrafish embryos and adult tissues were analyzed at whole genome-wide level to evaluate the functional activity of DrERVs in physiological process. The expression pattern of DrERVs in embryos was analyzed using the RNA-seq data extracted from European Nucleotide Archive. Data of four important developmental stages of segmentation (bud), pharyngula (28-h postfertilization [hpf]), hatching (2-days postfertilization [dpf]) and larval (5 dpf) were chosen. A total of 319 DrERVs with relatively high expression level (TPM  >  100) were identified at four development stages  of this type was highly expressed in embryos, which means that most of the active DrERVs in embryo have coding potential. Among the DrERVs expressed in embryos, 10 class I, two class II, and three class III DrERVs were identified. Among them, six class I and one class III were downregulated at 5 dpf, whereas the others were upregulated. Furthermore, the expression of DrEnv1–4 was analyzed. The result showed that some of the DrEnv1 and all of the DrEnv2 were expressed at the bud stage, whereas most of the rest DrEnv1 began to be highly expressed at 5 dpf . The DrEnv3 has broad and diverse expression patterns in embryos, from 28 hpf to 5 dpf, and most of them reached the peak expression at 28 hpf or 2 dpf except ERV-E15.5.82-DanRer, ERV-E4.7b.6E-DanRer, and ERV-E19.1.80-DanRer, which reached the peak expression at 5 dpf. The findings suggest the functional diversity of DrEnv3 group members. By contrast, the expression pattern of DrEnv4 showed high homogeneity; all of the members reached relatively high expression levels at a late period of embryo development (5 dpf) and exhibited a gradual increase in expression pattern during early development. Given that some previous studies suggested that ERVs could act as regulatory elements for adjacent genes in development, we next analyzed the adjacent genes (within 10 Kb) of bud-specific DrERVs. Expectedly, 110 known genes were found, 49 of which were expressed at the early stage and downregulated before 5 dpf (Table S4). Interestingly, 22 of the 49 genes were correlated with nucleic acid binding, and nine genes were correlated with ion binding. Further study is needed to elucidate the potential mutual regulation between DrERVs and their adjacent genes.The transcriptional expression profile of r period . The expc DrERVs . The resDrERVs in seven tissues, namely, heart, spleen, head kidney, liver, gut, brain, and muscle, were further evaluated by RNA-seq. Ninety-six highly expressed (FPKM > 1) DrERVs were identified in the seven tissues  were class I DrERVs that contain the DrEnv4 genes and account for 87% (27/31) of the total DrEnv4-containing DrERVs identified in zebrafish. This finding suggests that DrEnv4 members may play particularly important roles in cardiac function and metabolism. In this respect, we performed a trans-analysis of the 27 heart-specific DrEnv4-containing DrERVs. We found by enrichment analysis that the genes co-expressed with these DrEnv4-containing DrERVs were remarkably enriched in ATP metabolism and cellular respiration  were specifically expressed in the brain, and the encoded DrEnv3 proteins have the most intact structure of a typical envelope protein. Notably, among the 96 DrERVs expressed in seven tissues, 39 were also expressed in embryo (DrERVs exhibited an increased expression pattern or started expressing at 5 dpf (Table S6). This result suggests that few DrERVs expressed in adult tissues were expressed in embryos at early stages  challenge to explore whether DrERVs are involved in host antiviral immunity. For this purpose, the head kidney, spleen, and gut, which are the main immune organs that are representatives of central, peripheral, and mucosal immune organs, were selectively examined. The induced-expression of type I interferon (IFNφ1 and IFNφ3) and interferon-stimulated genes (ISG15 and mxb) in the head kidney, spleen, and gut was determined as indicators for the successful initiation of antiviral immunity in response to SVCV infection  4-9 (R = 0.95) and ighv4-8 (R = 0.88). ERVL-3.4.71-DanRer and ighv4-9 have a more significant correlation but a longer distance than that between ERVL-3.4.71-DanRer and ighv4-8, which indicates a possibility that DrERVs are correlated with the selection of variable regions in immunoglobulin heavy chain. The trans-acting genes were filtered by correlation coefficient (−0.99 > R > 0.99), and a set of 963 genes was generated. A group of G-protein coupled receptors (GPCRs) were found to be functionally correlated with DrERVs by gene ontology (GO) enrichment analysis . Given that GPCRs play important roles in various physiological processes, including immune and nervous activities, the discovery of the correlation between DrERVs and GPCRs may provide new insights into the involvement of DrERVs in cellular activities through association with GPCRs.We examined the expression profile of nfection . A totalDrERV-aid genes, namely, fga, ddx41, ftr35, igl1c3, and tbk1, which are located inside five DrERVs, namely, ERVL-1.2.11-DanRer, ERVL-9.1.84-DanRer, ERVL-2.7.54-DanRer, ERVL-3.7.49-DanRer, and ERVL-4.1.2-DanRer. The expression of fga and ddx41 was upregulated in the gut, and the expression of ftr35, igl1c3, and tbk1 was upregulated in the head kidney and spleen. These genes are potentially regulated by various TFs via association with cis-acting elements (such as promoters and enhancers) in the 5′-LTRs and/or 3′-LTRs of the five DrERVs. The binding sites of RelA, STAT4, NF-κ B, and IRF1 were found in the 5′-LTR of ERVL-1.2.11-DanRer, which is distributed upstream of the fga gene. An IRF2 binding site was found in the 5′-LTR of ERVL-9.1.84-DanRer, which is located upstream of the ddx41 gene. The binding sites of STAT4, STAT5a, STAT5b, IRF1, RelA, and NF-κB were found at the 5′-LTR of ERVL-2.7.54-DanRer, which is distributed upstream of the ftr35 gene. RelA, IRF1, IRF2, and NF-κB binding sites were located at the 5′-LTR of ERVL-3.7.49-DanRer, which is upstream of the igl1c3 gene. Interestingly, numerous binding sites for STAT4, STAT5a, STAT5b, STAT1β, NF-κB, RelA, IRF1, and IRF2 were found at the non-coding region between the 5′-LTR and 3′-LTR of ERVL-4.1.2-DanRer, which is distributed upstream of the tbk1 gene (fga and igl1c3 genes in ERVL-1.2.11-DanRer and ERVL-3.7.49-DanRer were selectively examined by chromatin immunoprecipitation (ChIP) assay to confirm the binding activity of TFs to the LTRs of DrERVs. We initially verified the upregulated expression of fga and igl1c3 in gut and head kidney tissues under SVCV infection , such as DrERVs that encode ncRNAs and PCGs (We believe that ERVs participate in cellular functions through three ways: providing transcription factor (TF)-binding sites for downstream genes and encoding regulatory noncoding-RNAs (ncRNAs) and functional proteins. We examined the remarkably upregulated immune-relevant genes in response to SVCV infection to verify the first mechanism. We found five potential bk1 gene . The assnfection . ChIP annfection . Thus, tand PCGs .DrERV elements with non-coding ability, especially those located at intergenic regions, to identify DrERV-derived ncRNAs. The result showed that 14 DrERVs strongly expressed ncRNAs in three tissues upon SVCV infection (Table S8). Among them, ERVL-7.2.48-DanRer and ERVL-3.1.72-DanRer were bidirectionally expressed, with a potential to form double-stranded RNA (dsRNA) (262 for ERVL-7.2.48-DanRer and (AT)31 for ERVL-3.1.72-DanRer. These SSR elements may potentially participate in transcription regulation. Pattern recognition receptors, such as RIG-I and MDA5, can recognize cytoplasmic dsRNAs under virus infection. The dsRNA transcripts derived from ERVL-7.2.48-DanRer and ERVL-3.1.72-DanRer were remarkably upregulated under SVCV stimulation (DrERV-derived dsRNAs could facilitate the activation of innate immunity as virus mimicry.We examined virus-responsive  (dsRNA) . ERVL-7.mulation . Thus, wDrERVs with protein-coding potential were regulated in the spleen, kidney, and gut tissues in response to SVCV infection (Table S9). Almost all the 41 protein-coding DrERVs potentially encode entire or partial Pol; 12 of these DrERVs encode Gag, and two of these DrERVs encode Env. Both of the two Env proteins belong to the DrEnv3 group. Besides, five of the 41 DrERVs encode a SCAN domain-containing protein. The SCAN domain is usually found in zinc-finger proteins and thought to be related to transcription regulation. The sequences that encode the SCAN domain-containing proteins are located between 5′-LTRs and pol genes in the five DrERVs; such a genetic locus is similar to that of gag gene, and this domain is proposed to be derived from gag  and their respective distance. It is worth noting that RetroTector does not properly assess solo LTRs, thus this highly defective type of DrERV is almost absent in this research. Additionally, the accurate prediction of LTRs is still challenging due to the high divergence. Although the SweepDNA and LTRID modules in RetroTector use various strategies to avoid false positive identification of LTRs, we believe that there may still be a certain misrecognition rate at the present stage. Clarification on these issues also depends on methodological innovation in the future.We systematically identified ERVs in a zebrafish model to understand the origin, evolution, and potential function of ERVs in an ancient vertebrate. Approximately 3,315 research , 55. In DrERVs have a remarkable distribution bias on chromosome 4, especially on the long arm of this chromosome. ERVs are highly enriched on sex-determination chromosomes in humans and other mammalian species, and some previous studies have suggested that chromosome 4 might be related with sex determination in zebrafish  in these elements. DrGD1 and DrGD2 were detected in DrERVs, XRVs, and mammalian ERVs. Therefore, these two domains are relatively conserved in evolution and could become new functional cores. In addition, these domains could also be applied as new markers for ERV identification in lower vertebrates. Since the discovery of syncytin in mammals, endogenous Env protein has received much attention  were detected. The results suggest that ERV elements could also be preserved during vertebrate evolution like normal genes and these ERV elements are very likely to play fundamental roles in biological activities. Besides that, these analogous elements are also possibly derived from large-scale cross-species transmissions.More than 88% of the BLAST hits are located in the intergenic regions when the RT elements of nfection ; thus, iDrERVs were actively expressed in embryos and adult tissues under physiological and viral infection conditions. These DrERVs account for 20.06% of the total DrERVs in zebrafish. The results suggest the extensively involvement of DrERVs in the life activities of zebrafish, including embryonic development, cellular metabolisms, tissue homeostasis, and immune responses. Among the 665 actively expressed DrERVs, 319 DrERVs were detected in embryos at four developmental stages, 96 DrERVs were found in seven adult tissues under normal physiological conditions, and 421 DrERVs were strongly induced in three tissues upon viral infection. The majority of embryo-specific DrERVs were differentially expressed at the four developmental stages, namely, bud, 28 hpf, 2 dpf, and 5 dpf. These DrERVs show distinct stage-specific transcriptional patterns during zebrafish development. The stage-specific genes or elements are closely related to cell lineage specification for ongoing development; therefore, the identification of lineage-specific DrERVs from each developmental stage needs to be further explored. A clarification on this issue would provide new insights into the mechanisms underlying ERV-based regulation of embryonic development. The 96 tissue-expressed DrERVs were mostly enriched in the heart, followed by the spleen, gut, brain, muscle, head kidney, and liver. Among these 96 DrERVs, 15 DrERVs were ubiquitously expressed in different tissues, whereas 48 DrERVs were expressed in specific tissues. The tissue-specific DrERVs were most abundant in the heart, followed by spleen, gut, head kidney, muscle, and liver. The tissue-expressed DrERVs exhibited a wider encoding potential for Env, Pol, and Gag proteins and noncoding RNAs. This encoding potential meets the requirement for the functional diversification of different tissues. In addition, 38 DrERVs expressed in adult tissues were also transcribed in embryos, and most of them were detected at 5 dpf. This finding suggests that these DrERVs play important roles in fundamental cellular activities throughout the lifetime of zebrafish from the late-developmental embryos to adult tissues. Notably, considerable numbers of embryo- and tissue-expressed DrERVs belong to class I DrERVs. Hence, this type of DrERV has stronger functional activities in cellular development and metabolism than those of other types.A total of 665 DrERVs were remarkably induced in head kidney, spleen, and gut tissues in response to SVCV infection. Most of these DrERVs were not transcribed in tissues at steady state under normal conditions without SVCV stimulation; hence, they are viral-responsive DrERVs, which are crucial for antiviral immunity in zebrafish. Given that the head kidney, spleen, and gut are three major immune-relevant tissues that represent the central, peripheral, and mucosal immune systems in fish, the vastly induced expression of DrERVs in these tissues suggests that DrERVs play extensive roles in a wide spectrum of immunities, which potentially rang from the activities in the early hemopoietic regulation, proliferation, and differentiation of immune cells in systemic immunity to local defense reactions in mucosal immunity. The correlation between ERVs and exogenous viruses has long been a challenging topic that remains to be explored. Some previous investigations have focused on the interplay between ERVs and XRVs, such as HIV, spleen necrosis virus, MuLV, and friend virus  of ERV expression, the sensing and control of ERVs by innate-immune signaling pathways and underlying mechanisms, the regulation of innate immunity by ERVs, the evolutionary history of ERVs, and the co-evolution mechanism between ERVs and host immunity.Importantly, 421 nd virus . Howeverenv, but potentially autonomous; nonautonomous elements that lack coding sequences but retain essential cis-acting sequences for transcription, packaging, and primer binding; and solo LTR products of recombination between LTRs and the associated loss of the internal domain and one LTR copy  and light chain (igl1c3) of zebrafish immunoglobin-coding sequences are closely correlated with DrERVs; and a considerable number of DrERVs regulate the expression of adjacent genes. These observations suggest the long-distance modulatory effect of DrERVs on remote target genes probably through regulatory elements, such as enhancers in LTRs. Thus, the vast majority of LTR structures in zebrafish genome may provide a large reservoir of regulatory elements for host utilization in various cellular activities and even long-distance genomic recombination, which leads to increased mutation frequency and thus contributes to species evolution  were bred and maintained in circulating water at 28°C under standard conditions as previously described . The sequences of each chromosome were segmented into 9 Mb fragments with 2 Kb overlapping regions between the fragments and submitted to RetroTector (http://retrotector.neuro.uu.se/) for prediction of DrERVs with default settings. RetroTector contains three modules for the recognition of candidate LTRs, the recognition of retroviral conserved motifs that meet distance thresholds and the reconstruction of original protein sequences. In addition, RetroTector can give a variety of possible ORFs and score values based on how well the sequences match the infectious retroviruses (Sequences of 25 zebrafish chromosomes (GRCz11) were downloaded from NCBI Genome database (oviruses .DrERVs are named following the rules described previously (Danio rerio) constitute the first and third parts, respectively. In this research, only the DrERVs related to class I–class III are initialed with “ERV”, whereas the others are initialed with “ERVL” (ERV-like). The second part indicates the locus. For example, in “ERV-E5.1.38-DanRer,” “5” represents chromosome 5, “1” represents the first 9 Mb fragments of chromosome 5, “38” represents the 38th DrERV in this fragment. In the DrERVs related to class I–class III, the second parts are initialed with “E” (epsilon-related), “AB” , or “S” (spuma-related). Some DrERV genes that encode for Gag, Pol, and Env proteins are located beyond the expected DrERV regions (from 5′-LTR to 3′-LTR); these genes are annotated independently with additional “G,” “P,” or “E” at the end of the second part of the name, for example, “ERV-21.2.63E-DanRer.”eviously . Briefly2 test was performed using expected DrERV number per megabase  and observed numbers per megabase (χ2 = ∑ [(observed − expected)2/expected]) to investigate the preference of DrERV distribution on chromosomes. The locations of NLR elements on chromosome 4 were indicated by the BLAST hits of FISNA, NACHT, LRR, and SPYR in the Pfam database (http://pfam.xfam.org/).The correlation among element number, chromosome length, and GC content was analyzed using SPSS 17.0. χpol genes were applied for the analysis as described previously (40–https://www.ncbi.nlm.nih.gov/cdd/). The phylogenetic tree was constructed using DNA sequences of 968 predicted RT regions in DrERVs and 134 reference sequences from alpha-, beta-, delta-, gamma-, epsilon-, and spuma-retroviruses, and Gypsy, Copia, Bel elements, and ERVs from other species (Table S10). The reference sequences were retrieved from NCBI (https://www.ncbi.nlm.nih.gov/) and Repbase (https://www.girinst.org/). A gag-tree was constructed with DNA sequences of 454 retrotrans_gag domains of gag genes in DrERVs, as well as some XRVs and ERVs from other species. The XRVs and ERVs from other species were selected by BLAST search using retrotrans_gag domains in DrERVs, including NM_001040611.1, NM_001291326.1, XM_027102482.1, XM_029234152.1, XM_028119014.1, XM_021000084.1, XM_027848720.1, NM_001040152.2, EU726524.1, GU120138, NC_001452.1, and NC_001802.1. The env-tree was constructed with DNA sequences of TLV_coat/HR1-HR2 domains in 71 env genes, as well as some sequences selected by BLAST hits of these env genes, including DQ247958.1, XM_018224752.1, XM_016661903.1, NC_007654.1, XM_029730443.1, MG981046.1, XM_030132418.1, XM_031283908.2, XM_029056457.1, JX412978.1, NM_001305591.1, JN587107.1, XM_027598904.1, JN587101.1, NM_001305590.1, XM_030548363.1, XM_022686469.1, XM_028746725.1, KR049171.1, and XM_019290776.2. Sequences were aligned using MAFFT 7 with default settings /2, where T is the invasion time (million years), D is the 5′- and 3′-LTR divergence given as the number of differences per nucleotide per site , and R is the genomic substitution rate per site per year. D was calculated using MEGA 6.06, the neutral rate of fish genomic evolution of 1.46 × 10−8 was applied . Conserved domains in these ORFs of gag and env were further identified by CDD. Considering all retrotrans_gag-containing gag are Gypsy-like, we identified 55 ORFs at the gag loci in DrERVs without recognizable retrotrans_gag domains. The ML tree was constructed based on amino acid sequences of these ORFs as described in classification and phylogenetic analysis of DrERVs. The best-fit model of VT+I+G4 was applied. Additional sequences of XRVs and ERVs were selected by BLAST results, including EGV97139.1, AII72209.1, AAO62318.1, AGV92852.1, AAO46144.1, AAC78248.1, ADC92307.1, NC_043194.1, NC_001867.1, and NC_001724.1. For the gag genes without recognizable domains, we identified undiscovered conserved domains with MEME Suite (https://itol.embl.de/). The ML tree of env genes constructed in classification and phylogenetic analysis of DrERVs was reused here for subsequent analysis. The conserved motifs in Env proteins were identified by comparing with the well-characterized Env proteins as reported previously  per fish, and spleens were collected 12 hpi. Total RNAs were extracted using TRIzol Reagent (Invitrogen). The first strand was synthesized according to manufacturer’s protocol of the Single Cell Full Length mRNA-Amplification Kit . The ERV-E5.1.38-DanRer-env sequence was amplified by using specific primers and nested primers as shown in Table S11. The PCR products were purified from 1.2% agarose gel by using gel extraction kit (Omega) and inserted into pGEM-T EASY vector (Promega), then sequenced. Then, sequences were assembled manually and compared with genomic sequence.Ten zebrafish were injected with 5 μL SVCV (10http://www.ensembl.org) database. The similarity between the queries and the hits were evaluated by scores and E-values provided by Ensembl. The RT sequences of ERV-E4.8.38-DanRer and HERV9NC-int were used to BLAST the genomes of platypus (mOrnAna1.p.v1), shark , lizard (AnoCar2.0), mouse (GRCm39), duck (CAU_duck1.0), chicken (GRCg6a), koala (phaCin_unsw_v4.1), dog (CanFam3.1), and cow (ARS-UCD1.2) in Ensembl. The BLAST hits with highest similarity  with ERV-E4.8.38-DanRer or HERV9NC-int were selected for phylogenetic analysis. A ML tree was constructed based on the amino acid sequences as described in Classification and phylogenetic analysis of DrERVs, with the best-fit model of LG+G4.After removing the identical RTs, a total of 665 non-redundant RT sequences were used as queries to BLAST the human genome (GRCh38) in Ensembl (PRJNA154389) (7 TCID50/mL) or mock PBS per fish, and RNAs were extracted as mentioned above. RNA-seq transcriptome libraries were prepared following TruSeq RNA sample preparation Kit from Illumina , and mRNAs was isolated by oligo(dT) beads and then fragmented by fragmentation buffer. Double-stranded cDNA was synthesized using a SuperScript double-stranded cDNA synthesis kit  with random hexamer primers (Illumina). Libraries were sequenced with the Illumina NovaSeq 6000 sequencer (2 × 150 bp read length). Then, reads were mapped to zebrafish reference genome (GRCz11) using TopHat; and quality control was performed using RseQC. The pattern recognition and clustering analyses were performed using scripts of R; differential expression was analyzed using DESeq, scripts of R and perl. Transacting analysis for ERV-like elements was performed using R script. The Pearson correlation coefficient and P value of expression level of ERV-like elements and mRNAs were assessed, and absolute value of Pearson correlation coefficient greater than 0.85 and P value less than 0.01 is considered transacting. GO enrichment was performed using the R topGO package. The mapping between Ensembl IDs and GO terms was retrieved from the Ensembl database using a custom Perl script (get_ensembl_go_terms.pl) from the topgo-wrapper repository .RNA-seq data of zebrafish embryo developmental stages was extracted from European Nucleotide Archive (A154389) . The dathttp://www.ensembl.org). Total RNAs were extracted from zebrafish spleen by using TRIzol Reagent (Invitrogen) and reverse-transcribed into cDNAs, then IRF1 and RelA cDNAs were generated through RT-PCR. The PCR products were purified from 1.2% agarose gel by using gel extraction kit (Omega), and inserted into the pcDNA6 (Invitrogen) and pEGFP-N1 (BD Biosciences) vectors. The plasmids were transformed into competent Escherichia coli DH5α (Invitrogen), and the positive plasmids were purified by using endo-free plasmid minikit II (Omega Bio-tek).The primers for zebrafish IRF1 and RelA were designed according to sequences in Ensembl  on a Mastercycler ep realplex machine (Eppendorf). SVCV infection and RNA preparation were performed as described in RACE, and RNAs were reverse-transcribed into cDNAs. PCR experiments were performed in a total volume of 10 μL by using a SYBR Premix Ex Taq kit (TaKaRa Bio). The reaction mixtures were incubated for 2 min at 95°C, then subjected to 40 cycles of 15 s at 95°C, 15 s at 60°C, and 20 s at 72°C. The relative expression levels were calculated using the 2−ΔCt and 2−ΔΔCt method with β-actin for normalization. Each PCR trial was run in triplicate parallel reactions and repeated three times.The transcriptional expression of DrERVs surrounding immune-related genes with PROMO  per embryo at 24 hpf. At 36 hpf, 30 embryos were collected for each replicate in both PBS and SVCV administered groups (three replicates in each group). ChIP assays were carried out according to the manufacturer’s protocol of the ChIP assay kit . Samples with normal mice IgG and the input were used as negative and positive controls. Pull-down levels of target promoter sequences were determined by qPCR and normalized to the corresponding abundance in the input chromatin. The promoter-specific primers of indicated DrERVs are listed in Table S11.Promoters were predicted for th PROMO , 77. ChIt test for paired samples. The P values *, P < 0.05, **, P < 0.01, and ***, P < 0.001 were considered statistically significant.Statistical analysis and graphical presentation were carried out using SPSS 21.0 and GraphPad Prism 6.0. Quantitative data from the three independent experiments were expressed as mean ± SD. The groups were compared statistically using Student's PRJNA690124 (for expression profile of 7 tissues) and PRJNA690234 (for expression profile in response to SVCV infection).Raw data of RNA-Seq have been deposited into (Sequence Read Archive (SRA)), with the accession number


PRAG1, MFHAS1, PPP1R3B, TNKS, MSRA, PRSS55, RP1L1, PINX1, MTMR9, FAM167A, BLK, GATA4, and CTSB). These results strengthen the hypothesis that a set of variants located on ch 8p23.1 that result from positive selection during early admixture events may influence obesity-related disease predisposition in admixed individuals of the Brazilian population. Furthermore, we present evidence that the exploration of local ancestry deviation in admixed individuals may provide information with the potential to be translated into health care improvement.We recently reported a deviation of local ancestry on the chromosome (ch) 8p23.1, which led to positive selection signals in a Brazilian population sample. The deviation suggested that the genetic variability of candidate genes located on ch 8p23.1 may have been evolutionarily advantageous in the early stages of the admixture process. In the present work, we aim to extend the previous work by studying additional Brazilian admixed individuals and examining DNA sequencing data from the ch 8p23.1 candidate region. Thus, we inferred the local ancestry of 125 exomes from individuals born in five towns within the Southeast region of Brazil , and compared to data from two public Brazilian reference genomic databases, BIPMed and ABraOM, and with information from the 1000 Genomes Project phase 3 and gnomAD databases. Our results revealed that ancestry is similar among individuals born in the five Brazilian towns assessed; however, an increased proportion of sub-Saharan African ancestry was observed in individuals from Belo Horizonte. In addition, individuals from the five towns considered, as well as those from the ABRAOM dataset, had the same overrepresentation of Native-American ancestry on the ch 8p23.1 locus that was previously reported for the BIPMed reference sample. Sequencing analysis of ch 8p23.1 revealed the presence of 442 non-synonymous variants, including frameshift, inframe deletion, start loss, stop gain, stop loss, and splicing site variants, which occurred in 24 genes. Among these genes, 13 were associated with obesity, type II diabetes, lipid levels, and waist circumference ( Admixture between different continental populations generates mosaic chromosomes comprised of genomic segments with different ancestry, which is defined as local ancestry . As a reThe Brazilian population was formed via an admixture process comprised mostly of European, sub-Saharan African, and Native-American population ancestry. In terms of global ancestry inference, studies have shown a predominance of European ancestry, followed by sub-Saharan African and Native-American . FurtherInterestingly, the ch 8p23.1 region found to be under positive selection in the Brazilian population has been reported to contain genes previously associated with type 2 diabetes and overweight/obesity in admixed Americans . Indeed,Therefore, our objective was to expand our knowledge of the effects of admixture by describing the genetic variability of ch 8p23.1 from admixed Brazilian exomes compared with global populations. To achieve our aim, we first extended our study to additional admixed exomes from other southeastern Brazil towns. Second, we identified and analyzed sequencing variants identified in the candidate region of ch 8p23.1.N = 30); Ribeirão Preto (N = 30), located in the state of São Paulo; and Belo Horizonte (N = 28), the capital of the state of Minas Gerais  files created using the GRCh37 assembly. We used PLINK 1.9  softwareWe evaluated the heterozygosity rate of each individual to search for inbreeding (low heterozygosity rate) or sample contamination (high heterozygosity rate) , and indAfter genotype and individual filtering, a total of 893 exomes and 661,617 variants remained in the Brazilian datasets analyzed. We merged this dataset with the 1000 Genome project data phase 3 (1KGP)  and remoTo evaluate whether our Brazilian sample (BRS) presents a geographical substructure based on birthplace, we performed the analysis of molecular variance (AMOVA) using the poppr.amova package in R software , which c1  (We tested our exome sample for positive selection by the same approach used previously . Brieflyerived|) , interpoerived|) , and poperived|)  based onerived|)  in a sinerived|) . The varWe extracted the ch 8p23.1 region (8092025–11859740 bp)  from theWe included the allele frequency (AF) information from African/African-American (AFR/AFA), Latino/admixed American (LAT/AMR), East Asian (EAS), non-Finish European (NFE), and South Asian (SAS) populations from the gnomAD exome dataset ; sub-Sah2. Functional Analysis through Hidden Markov Models (FATHMM)  , PhD-SNP(FATHMM) , Condel (FATHMM) , PANTHER(FATHMM) , Align G(FATHMM) , and SNP(FATHMM) . For Ali® database.Associated trait information for genes located on ch 8p23.1 was accessed from the NHGRI-EBI GWAS Catalog  on Octobp = 0.0001), indicating the absence of a population substructure, which is consistent with the lack of clusters observed in the PCA of the BRS sample that was based on birthplace . The proportion of the sample that comprised the AFR component was 16.0% (SD = 1.1%), and the NAT component was 9.4% (SD = 1.1%) (SD = 6.0%), and the highest AFR component . São Paulo, in contrast, had the greatest proportion of EUR ancestry  and the lowest AFR proportion . The NAT component of the sample remained constant among individuals from the different towns and the two public Brazilian databases, ranging from a mean of 4.6% (SD = 2.8%) in Barretos to 8.2% (SD = 1.3%) in the BIPMed sample  . We obsed sample . Our assd sample .We inferred the inversion events on ch 8p23.1 from the exome data by the same approach used in our previous report , with thWe tested for positive selection in the exome dataset using the Fisher combined scores (FCS). FCS, which includes PBS tests in the calculation, this is the same approach used in our previous work . HoweverRP1L1 gene in the ABraOM database contained the largest number of exclusive Brazilian variants , type 2 diabetes mellitus (T2DM), obesity, insulin resistance, body mass index (BMI), body fat distribution, waist circumference, and diet measurement , MFHAS1, ERI1, PRSS55, RP1L1, PINX1, FAM167A, GATA4, and CTSB  were found in 13 genes, which were previously associated with metabolic phenotypes such as type 1 diabetes mellitus .The sequencing analysis of ch 8p23.1 performed in the current study revealed the presence of 442 non-synonymous variants, including frameshift, inframe deletion, start loss, stop gain, stop loss, and splicing site variants, which occurred in 24 genes and two open reading frames. Among the genes, 13 were associated with obesity, type II diabetes, lipid levels, and waist circumference  or EUR-NAT-EUR (n = 98) ancestry haplotypes compared to NAT-NAT-NAT haplotypes (n = 118). Therefore, our results suggest that interactions among EUR or AFR ancestry genes in adjacent regions on ch 8p23.1 with the NAT ancestry core seems not to be enough to boost negative or positive selection in our sample. However, gene interactions can occur among genes on ch 8p23.1 and genes on other regions of the genome, and further studies should be performed to clarify this issue.Furthermore, when considering a polygenic phenotype, one aspect that we should take into account is the presence of epistatic interactions. Thus, we could argue that an increase in the frequency of the genes of NAT ancestry on ch 8p23.1 could be due to the breakup of negative epistatic interactions among genes on other regions from NAT genomes and the genes on ch 8p23.1, which are currently coupled with AFR and EUR ancestry tracts, and could lead to increased fitness. We count the number of AFR-NAT-AFR, EUR-NAT-EUR, and NAT-NAT-NAT haplotypes, including ch 8p23.1 and adjacent regions (approximately 3.7Mb upstream and downstream ch 8p23.1). However, we did not observe an overrepresentation of AFR-NAT-AFR (We successfully replicated previous results that identified local ancestry deviation on ch 8p23.1, which seems to have occurred in populations from the southeastern region of Brazil, including the states of São Paulo and Minas Gerais. Thus, the candidate region on ch 8p23.1 emerges as a hotspot for obesity-related genes in admixed Brazilians, which should be further explored. In particular, the information presented here could be used in the future to support risk stratification and implement personalized public health policies and preventive medical treatments.The datasets presented in this study can be found in online repositories have been included in the The studies involving human participants were reviewed and approved by Comit de tica da Universidade Estadual de Campinas. The patients/participants provided their written informed consent to participate in this study.in silico prediction analysis. CR participated in BIPMed data acquisition. MN and MZ participated in the ABraOM data acquisition. LD and MB participated in the Belo Horizonte data acquisition and determined sample information. VV aided with the Barretos data acquisition and provided sample information. WS aided in the Ribeirão Preto data acquisition and provided sample information. IL-C conceptualized the work and served as the principal investigator. All authors reviewed and approved the final version of the manuscript.RS created the study design, conceptualized the work, and performed data acquisition and analysis. MG performed the 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.


Young people who inject drugs (PWID) have higher HCV incidence and lower treatment initiation rates compared to their older peers. Novel, simplified care models need to be developed to engage, treat and cure hard to reach patient populations, such as young PWID.HCV-Seek Test & Rapid Treatment (HCV-ST&RT) for curing HCV in young PWID. Eligible participants were 18-29 years of age, HCV Ab+, treatment naïve, and had injected drugs in the past 30 days. Participants were randomized 1:1 to the Rapid Treatment or Usual Care arm. Participants randomized to Rapid Treatment received a same-day medical evaluation, confirmatory and baseline lab testing, and 7-day starter pack of sofosbuvir/velpatasvir. Participants in Usual Care received same-day HCV confirmatory testing and, if positive, facilitated referral to local providers. The primary endpoint was sustained virologic response (SVR12) in RNA+ participant within 12 months of enrollment. We present final data from the randomized pilot clinical trial Among 47 eligible participants, 38 were enrolled and randomized. 14/18 in the Rapid Treatment arm and 11/20 in the Usual Care arm were confirmed HCV RNA+ and included in the intention-to-treat analysis. Demographics of the RNA+ participants were similar in the two arms with a mean age of 26 years; 24% women; 36% Hispanic and 4% non-Hispanic black. At baseline 24% were homeless, 52% received medication for opioid use disorder in the prior 90 days, and participants injected a median of 20 of the last 30 days. In the intention-to-treat analysis, 9/14 (64%) of the Rapid Treatment arm and 2/11 (18%) of the Usual Care arm had confirmed SVR12 (p=0.042). Of the 5 participants in the Rapid Treatment arm who did not achieve SVR12, 1 had treatment failure, 1 never started DAA therapy, 1 had an on-treatment response with pending SVR12 confirmation, and 2 were lost to follow-up. Among young HCV RNA+ PWID, significantly higher rates of cure were achieved using the Rapid Treatment model with same day, low-threshold, simplified HCV care compared to facilitated referral. Meeting young PWID where they’re at and initiating HCV treatment ‘in the moment’ without the need for repeat visits appears to be a promising strategy for treating this hard to reach population.Benjamin Eckhardt, MD, MS, Gilead Sciences (Grant/Research Support) Shashi Kapadia, MD, Gilead Sciences Inc (Grant/Research Support) Kristen Marks, MD, Gilead Sciences (Grant/Research Support)


We investigated the correlation between texture features extracted from apparent diffusion coefficient (ADC) maps or diffusion-weighted images (DWIs), and grade group (GG) in the prostate peripheral zone (PZ) and transition zone (TZ), and assessed reliability in repeated examinations.b-values of 0, 100, 1,000, and 1,500 s/mm2. Region of interest (ROI) for cancer was assigned to the first and second DWI acquisition separately. Texture features of ROIs were extracted from comma-separated values (CSV) data of ADC maps generated from several sets of two b-value combinations and DWIs, and correlation with GG, discrimination ability between GG of 1–2 versus 3–5, and data repeatability were evaluated in PZ and TZ.Patients underwent 3-T pelvic magnetic resonance imaging (MRI) before radical prostatectomy with repeated DWI using b-value combinations of 100 and 1,500 s/mm2 and 10% based on ADC map with b-value of 0 and 1,500 s/mm2 showed significant correlation with GG, acceptable discrimination ability, and good repeatability. In TZ, higher-order texture feature of busyness extracted from ADC map of 100 and 1,500 s/mm2, and high gray-level run emphasis, short-run high gray-level emphasis, and high gray-level zone emphasis from DWI with b-value of 100 s/mm2 demonstrated significant correlation, excellent discrimination ability, but moderate repeatability.Forty-four patients with 49 prostate cancers met the eligibility criteria. In PZ, ADC 10% and 25% based on ADC map of two Some DWI-related features showed significant correlation with GG, acceptable to excellent discrimination ability, and moderate to good data repeatability in prostate cancer, and differed between PZ and TZ.The online version contains supplementary material available at 10.1186/s41747-021-00252-y. Furthermore, there are concerns regarding the reliability of texture features which are sensitive to imaging characteristics, possibly having coincidental significance due to a larger number of parameters [Texture analysis of clinical imaging has been increasingly carried out to determine its correlation with histological findings, such as lesion aggressiveness and clinical outcome –3. Texturameters –6.Magnetic resonance imaging (MRI) is a primary imaging modality used for prostate cancer. Many studies have been reported regarding the correlation between DWI-related parameters and lesion aggressiveness, such as the Gleason score (GS) and grade group (GG), with inconsistent results. It was reported that ADC entropy showed significant difference between GS of 3 + 4 and 4 + 3 but not in ADC mean . Alessanb-value combinations or DWIs with several b-values, and GG in the PZ and TZ, separately, and to evaluate the reliability of texture features in repeated examinations.This study aimed to analyze the correlation between texture features extracted from ADC maps generated from several sets of two This study was compliant with Helsinki Declaration. The following inclusion and exclusion criteria were considered: Inclusion criteria: patients who underwent 3-T multiparametric MRI (mpMRI) at our institute, including two sets of repeated DWI acquisitions for evaluating prostate lesions with informed consent from July 2016 to May 2020. Exclusion criteria: treatment except radical prostatectomy; lesions with a longitudinal diameter < 10 mm; lesions not detected on DWI; lesions with a voxel number within the region of interest (ROI) < 50; lesions containing voxel with ADC value < 0; poor image quality. Figure MRI was performed using a 3-T system  with a pelvic phased-array coil. No endorectal coil was used. Either 20-mg hyoscine-N-butyl-bromide or 1-mg glucagon was injected intramuscularly before examination to minimize bowel peristalsis.b-values  with three orthogonal diffusion probing gradients were generated. ADC maps were generated using DWIs with b-values of 100 and 1,000 s/mm2, ADC map  in line with the Prostate Imaging–Reporting and Data System (PI-RADS) version 2.1 (https://www.acr.org/-/media/ACR/Files/RADS/PI-RADS/PIRADS-V2-1.pdf) for the first and second DWIs, respectively. The DWI sequence parameters are summarized in Supplemental Table SA routine mpMRI protocol was applied to all patients, including sagittal, coronal, and axial T2-weighted imaging; axial DWIs; and axial dynamic contrast-enhanced imaging before and after gadolinium chelate injection of 0.1 mmol/kg gadoterate meglumine, Magnescope, Dotarem . For DWI, two sequential free-breathing DWI single-shot spin-echo echo-planar images were acquired. The patient remained in the same position between the two DWI acquisitions. Four b-value of 1,500 s/mm2  and hypointensity on the first ADC map , referring to T2-weighted imaging, dynamic contrast-enhanced imaging, and whole-mount, step-sectioned histological evaluation of prostatectomy specimen. Then, the ROI was placed on the first DWI datasets of DWI 0, DWI 100, and DWI 1,000 through IVIM application of a Synapse Vincent 3D Image Analysis System. For non-peripheral transition zone (TZ) cancers, the polygonal two-dimensional ROI was manually determined on the lesion in the center slice showing hypointensity on T2-weighted images and hyperintensity on the first DWI 1,500, referring to the first ADC map , dynamic contrast-enhanced imaging, and whole-mount, step-sectioned histological evaluation of prostatectomy specimen. After this, the ROI was placed on the first DWI datasets of DWI 0, DWI 100, and DWI 1,000 through intravoxel incoherent motion (IVIM) application of the Synapse Vincent 3D Image Analysis System. The same procedures were repeated for the second DWI datasets. Voxel data distributions within the ROI were rendered in comma-separated values (CSV) format  using a Synapse Vincent 3D Image Analysis System. Then, the ADC of each voxel was calculated by fitting signal intensity decay between four patterns of b-value combinations using a monoexponential curve fit: 0 and 1,000 s/mm2, ADC ; 0 and 1,500 s/mm2, ADC ; 100 and 1,000 s/mm2, ADC ; and 100 and 1,500 s/mm2, ADC . Representative cases are shown in Figs. Image analysis including ROI assignment was performed by a consensus decision of two observers  using a Synapse Vincent 3D Image Analysis System . For PZ cancer, the polygonal two-dimensional ROI was manually determined on the lesion in the center slice showing hyperintensity on the first DWI with a We assigned a two-dimensional ROI in the center slice of the lesion because more than half lesions were not large enough to place a three-dimensional ROI. Only 21 lesions, 43% of total lesions, showed longitudinal diameter > 12 mm on images and could be determined on equal to or more than four slices  that would have satisfied assigning ROIs on two or more slices avoiding peripheral images, possibly being affected by partial volume effect. Texture analysis calculates the relationship between adjacent voxels, and thus, we assumed that appropriate texture analysis required at least four voxels along each direction.www.github.com/metavol/ptexture) written in Python language. The detailed methods are described elsewhere [All voxels within the ROI were extracted from the CSV data of ADC , , , and , and DWI 0, 100, 1,000, and 1,500. First-order statistical variables  were calculated. After discretization of voxel values (bin number 32), higher-order texture analysis was performed in a two-dimensional manner to generate a gray-level co-occurrence matrix (GLCM), gray-level run-length matrix (GLRLM), gray-level zone-size matrix (GLZSM), and neighborhood gray-level difference matrix (NGLDM). Homogeneity, energy, correlation, contrast, entropy, and dissimilarity were calculated from the GLCM. Short-run emphasis (SRE), long-run emphasis (LRE), low gray-level run emphasis (LGRE), high gray-level run emphasis (HGRE), short-run low gray-level emphasis (SRLGE), short-run high gray-level emphasis (SRHGE), long-run low gray-level emphasis (LRLGE), long-run high gray-level emphasis (LRHGE), gray-level non-uniformity for run (GLNUr), run-length non-uniformity (RLNU), and run percentage (RP) were calculated from GLRLM. Short-zone emphasis (SZE), long-zone emphasis (LZE), low gray-level zone emphasis (LGZE), high gray-level zone emphasis (HGZE), short-zone low gray-level emphasis (SZLGE), short-zone high gray-level emphasis (SZHGE), long-zone low gray-level emphasis (LZLGE), long-zone high gray-level emphasis (LZHGE), gray-level non-uniformity for zone (GLNUz), zone length non-uniformity (ZLNU), and zone percentage (ZP) were calculated from GLZSM. Coarseness, contrast, and busyness were calculated from NGLDM. Texture features were computed using the PTexture package  was calculated because there was a difference in prognosis between GG of 1 and 2, versus GG of 3, 4, and 5 [p-values < 0.05 were considered statistically significant.Statistical analyses were carried out separately for PZ and TZ cancers. First, the correlation between texture features and GG was evaluated using Spearman's rank correlation test. For the features showing significance at both the first and second examinations, receiver operating characteristic (ROC) curves for differentiating between GG of 1 and 2 4, and 5 . To checWe considered the following values for classifying the strength of correlation: moderate (|ρ|: 0.4-0.7), strong (|ρ|: 0.7-0.9), and very strong (|ρ|: 0.9-1) , discrimFrom July 2016 to May 2020, a total of 296 patients with suspected prostate cancer underwent mpMRI including two sets of repeated DWI acquisitions for evaluating prostate lesions with informed consent. Among them, 52 patients underwent mpMRI before prostatectomy and were histologically diagnosed as prostate cancer by the institutional pathologists. There were 62 cancers with a longitudinal diameter ≥ 10 mm. Furthermore, one lesion undetected on DWI, six lesions with a voxel number within the ROI < 50, three lesions with poor image quality either in the first or second DWI, and three lesions containing voxel with ADC value < 0 were excluded. Finally, 44 patients with 49 cancers were analyzed. The characteristics of patients and lesions are summarized in Table As a representative of ADC histograms, ADC 10% calculated from ADC , , , and  are summarized in Table versus GG of 3, 4, and 5, ICC and its 95% confidence interval, and Bland-Altman analysis (%) , are summarized in Table 3. Among them, as ADC 10%-based on ADC  and ADC  as well as ADC 25% based on ADC  showed moderate correlation coefficient with GG , acceptable discrimination ability (AUC > 0.7) at both examinations, and good data repeatability (ICC > 0.8). The correlation between GG and ADC 10% mean of the first and second examinations based on ADC , and their XY plot are shown in Fig. In PZ cancer, the following metrics showed significant correlation with GG at both examinations: ADC 10% and 25% based on ADC ; ADC 5%, 10%, and 25% based on ADC ; ADC 10%, 25%, and 50% based on ADC ; and ADC 5%, 10%, and 25% based on ADC . Other metrics including higher-order texture features did not show significance. The results, including Spearman's ρ and its 95% confidence interval, the AUC of ROC for differentiation between GG of 1 and 2 p < 0.05), excellent discrimination ability (AUC > 0.8) at both examinations, and moderate data repeatability . The correlation between GG, and busyness mean of the first and second examinations based on ADC  and HGRE mean of the first and second examinations based on DWI 100, and their XY plot are shown in Figs. For TZ cancer, SRHGE and busyness based on ADC 100, 1,500), and skewness, HGRE, SRHGE, LRHGE, HGZE, SZHGE, and busyness based on DWI 100, and skewness, HGRE, SRHGE, and HGZE based on DWI 0 showed significant correlations with GG. As opposed to PZ, the first-order statistical metrics did not show significance. The results, including Spearman's ρ and its 95% confidence interval, the ROC-AUC of for differentiating GG of 1 and 2 from GG of 3, 4, and 5, ICC and its 95% confidence interval, and Bland-Altman analysis (%)  are summarized in Table 00, and sversus GG of 3, 4, and 5, but also practical data repeatability between the PZ and TZ in prostate cancer.To our knowledge, this is the first study showing a difference in DWI-related texture features that demonstrate not only significant correlations with GG and discrimination ability between GG of 1 and 2, b-values , and measuring texture feature using different methods, could explain the differences. Baek T et al. [b-values of 0 and 1,000 s/mm2 showed significance with GS. The differences in analyzing the PZ and TZ together and the distribution of lesion aggressiveness , including 19 biopsy-proven lesions, might explain the discrepancy. When analyzed by combining PZ and TZ cancers, the entropy of GLCM based on ADC  did not show significance either in bin of 8, 16, or 32 setting .In PZ cancer, ADC 10% based on ADC  and  as well as ADC 25% based on ADC  satisfied moderate correlation and had acceptable discrimination and good repeatability. These results were in accordance with a systematic review reporting that ADC correlated moderately with GS  . HoweverT et al.  reportedIn TZ cancer, busyness based on ADC , and HGRE, SRHGE, and HGZE based on DWI 100 demonstrated moderate correlation coefficients, excellent discrimination, and moderate data repeatability. To evaluate the effect of bin number, texture features using bin 8 and 16 were also analyzed. Similar results were obtained . In general, texture features for TZ cancer tend to show higher correlation and discrimination but lower data repeatability than those for PZ cancer.b-value looks similar to fat-saturated T2-weighted imaging. However, it is unclear why DWI-related features showing significance with GG differ between PZ and TZ. One possible explanation might be that while the volume of the lumen and stroma is positively correlated with ADC, that of the epithelium is negatively correlated [Another important finding is that ADC histogram metrics such as 10%, which showed significance in PZ cancer, showed no significance in TZ cancer . This result was not inconsistent with the results of a systematic review, which reported that ADC correlated weakly  with GS in TZ cancer . Furtherrrelated . This mab-value combination is appropriate for calculating ADC, ADC generated from DWI 100 and 1,500 would be relevant in terms of a correlation with GG (Tables b-values of 50 and 1,500 s/mm2 using a mono-exponential method reported to show the highest AUC among the IVIM, kurtosis, and IVIM-kurtosis methods [Regarding which two G Tables  and 4. W methods , which iAnother focus of the present study is data repeatability. DWI-related features with significance for PZ cancer demonstrated good repeatability, but those for TZ cancer remained moderate. However, moderate repeatability may be acceptable in clinical practice. In a previous study, the κ value for the reproducibility of the PI-RADS 2 score in TZ was 0.525 .Texture features themselves have high potential with respect to correlation with lesion aggressiveness and clinical outcome. However, those have a tendency prone to be affected by a mild difference of the imaging data including artifacts. Therefore, reliability studies not only for observers but also for imaging data themselves should be verified sufficiently before being applied to clinical practice.This study has some limitations. First, we analyzed patients who underwent radical prostatectomy because of the clear correlation between histology and mpMRI, but this concept would have reduced the number of the cases and lesions included in the study. Second, texture features of T2-weighted imaging were not evaluated because matrix size was different from DWI and the voxel number in the ROI differed greatly. Third, texture features were extracted from two-dimensional ROI because the lesion size was not large enough to extract features from three-dimensional ROI. Fourth, ROI assignment was performed by consensus between two observers, not carried out independently. We consider consensus reading would be acceptable because one of the main purposes of the present study was to assess reliability of the imaging data themselves. Finally, in both PZ and TZ cancer, the number of lesions was not sufficiently large; therefore, further analyses by combining features through logistic regression and/or discriminant analyses were not performed.versus GG of 3, 4, and 5, but lower data repeatability than those for PZ cancer. Regarding a correlation with GG, DWI 100 and 1,500 s/mm2, and ADC generated from these two images would be relevant.In conclusion, some DWI-related features showed significant correlation with GG and clinically acceptable data repeatability in histologically confirmed prostate cancer, and they differed between the PZ and TZ. The texture features for TZ cancer tended to show higher correlation with GG and higher discrimination ability between GG of 1 and 2 Additional file 1:Supplemental Table 1 Acquisition parameters for diffusion-weighted imaging


Coronavirus disease 2019 (COVID-19) has become a new public health crisis threatening the world. Dysregulated immune responses are the most striking pathophysiological features of patients with severe COVID-19, which can result in multiple-organ failure and death. The cytochrome P450 (CYP) system is the most important drug metabolizing enzyme family, which plays a significant role in the metabolism of endogenous or exogenous substances. Endogenous CYPs participate in the biosynthesis or catabolism of endogenous substances, including steroids, vitamins, eicosanoids, and fatty acids, whilst xenobiotic CYPs are associated with the metabolism of environmental toxins, drugs, and carcinogens. CYP expression and activity are greatly affected by immune response. However, changes in CYP expression and/or function in COVID-19 and their impact on COVID-19 pathophysiology and the metabolism of therapeutic agents in COVID-19, remain unclear. In this analysis, we review current evidence predominantly in the following areas: firstly, the possible changes in CYP expression and/or function in COVID-19; secondly, the effects of CYPs on the metabolism of arachidonic acid, vitamins, and steroid hormones in COVID-19; and thirdly, the effects of CYPs on the metabolism of therapeutic COVID-19 drugs. Coronavirus disease 2019 (COVID-19), which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has become a global challenge. As of December 29, 2021, there have been over 281 million confirmed cases of COVID-19, including more than five million deaths, reported to the WHO . NumerouDysregulated immune response is the most striking pathophysiological feature in severe COVID-19 patients; characterized by cytokine storm and lymphopenia; resulting in acute respiratory distress syndrome (ARDS), multiple-organ failure, and even death. SARS-CoV-2 may activate both innate and adaptive immune responses in patients, including lymphopenia, cytokine storm, and abnormal activation of macrophages and their complementary system . Severe The CYP system is the most important drug metabolizing enzyme family existing amongst species, and plays a role in the metabolism of endogenous and exogenous substances . CYP enzCYPs are classified into two categories: endogenous (CYP family 7–51) and xenobiotic (CYP family 1–4) . EndogenCYP3A4, CYP2C9, CYP2C8, CYP1A2, and CYP2E1 are highly expressed in the liver, whilst, CYP2A6, CYP2D6, CYP2B6, CYP2C19, and CYP3A5 are less abundant in the liver. CYP2J2, CYP1A1, and CYP1B1 are mainly expressed extrahepatically .CYP gene expression is regulated by the activation of several nuclear receptors, including constitutive androstane receptor (CAR), pregnane X receptor (PXR) and aryl hydrocarbon receptor (AhR) . CYP expUntil now, no studies have focused on the effects of SARS-CoV-2 on the expression and activity of CYPs. However, previous studies have found that CYPs expression changed in several viral infections. CYP1A1 activity was suppressed by 75% in coxsackievirus B3 infected mice . CYP3A4 In vitro, CYPs were regulated  by multiple cytokine treatments, including IL-6, TNF-α, IFN-γ, TGF-β and IL-1β  mice . HoweverIn human hepatocytes, IL-6 also decreases both rifampicin- and phenobarbital-mediated induction of CYP2B6, CYP2C8, CYP2C9, and CYP3A4, by negatively regulating PXR and CAR gene expression . Severalvia CYP3A4, 2C9, and 2C19, but reduced the drug metabolism via CYP1A2 pyrene-induced CYP1A1 expression in rat liver epithelial WB-F344 cells . CYP3A11rodentium model of infectious colitis (A novel antagonist of soluble TNFα (XPro1595) selectively blocked the down-regulation of CYP3A11 and CYP3A25 mRNAs, as well as the induction of CYP2A4/5 in a C.  colitis . A recen colitis .Previous studies demonstrated that treatment of mice with IL-1, decreased CYPs contents . IL-1 rarodentium infection mice model and CYP2B9, CYP2D22, and CYP2E1 in a septic mice model  infection, and the exogenous supplement of AA in HCoV-229E-infected cells significantly suppressed HCoV-229E virus replication (AA is a polyunsaturated fatty acid produced from membrane phospholipids by phospholipase-A2 (PLA2) in inflammatory condition. AA-derived lipid autacoids, including prostaglandins (PGs), thromboxanes, and leukotrienes, are critical mediators in inflammation, and tissue homeostasis . An intelication .Aside from cyclooxygenase (COX) and lipoxygenase pathways, the CYP pathway is another important AA metabolism pathway . CYP4A1 Vitamins are essential dietary components due to their antioxidant properties and immunomodulatory effects, which are beneficial in various infectious diseases, such as COVID-19 . A recenVitamin A, also called retinoic acid (RA), exhibited a protective effect on HBV and measles virus infection . Yuan etVitamin Bs are important for the normal physiological functioning of body cells . A recenVitamin C is well known for its antiviral, antioxidant, anti-inflammatory and immunomodulating properties, which make it a potential therapeutic candidate against COVID-19 infection. Several recent studies show that most severe, or critically ill, COVID-19 patients had hypovitaminosis C, indicating that vitamin C can potentially be used as an adjunctive therapy in the critical care of COVID-19 patients .Vitamin D helps to maintain calcium–phosphorus metabolism and inhibits the overexpression of inflammatory cytokines such as IL-1α, IL-1β, TNF-α . Serum lCOVID-19 may predispose to venous and arterial thrombosis disease due to excessive inflammation or hypoxia. Vitamin K1 could potentially help combat thrombotic complications in COVID-19 patients, due to its ability to activate the coagulation system. A clinical study has also shown that a low vitamin K status was associated with mortality in patients with COVID-19 .Furthermore, multiple CYPs regulate vitamin metabolism. CYP26 enzymes are involved in the metabolism and elimination of vitamin A . ResearcRecent advances suggest endocrine system dysfunction in COVID-19 patients. Angiotensin-converting enzyme 2 (ACE2) and transmembrane serine protease 2 (TMPRSS2) are expressed in several endocrine tissues, including the hypothalamus, pituitary, thyroid, adrenal, gonads, and pancreatic islets , suggestOn the other hand, CYPs are important for catalyzing specific reactions of steroid precursors in the steridogenic pathway . CYP monSome COVID-19 patients, especially those with severe diseases, suffered from lung injury, kidney injury, even multi-organ failure. Numerous previous studies showed CYPs played a role in lung injury, kidney injury and liver injury, including CYPs we mentioned above that may affected in COVID-19, suggesting these CYPs may be involved in the pathophysiological process of severe COVID-19.Lung is the main target of SARS-CoV-2, and lung injury is common in severe COVID-19 patients. Increasing studies showed CYPs play a role in ALI. A recent study found that CYP1A1 knockout enhanced LPS-induced ALI, as evidenced by increased IL-6, TNF-α, IL-1β in lung . CYP1A1 via the vasodilating effects of 20-HETEs (CYPs metabolizes AA to EETs and 20-hidroxyeicosatetranoic acids (20-HETEs), which is believed to play a protective role in lung injury . CYP4A a20-HETEs .The incidence of AKI was about 8.9% in COVID-19 patients, but can reach 25% in critically ill patients .In the current COVID-19 pandemic, hepatic dysfunction has been observed in 14–53% of patients, particularly in severe cases . Hepatic injury interacted with CYP expression and activity. Liver diseases cause changes in the expression and activity of CYPs, while CYPs also implicated in hepatic injury. Induction of CYP2E1 enzyme is known to play a role in the pathogenesis of alcoholic liver disease and thioacetamide induced-liver injury . Several studies demonstrated that CYP2E1 inhibitor protects the liver against chemical-induced hepatic injury .Since the primary function of CYP1-3 enzymes is facilitating drug metabolism, the main concern of the dysregulation of CYP expression in COVID-19 is the direct impact on drug disposition and pharmacokinetics in humans. Currently, there is no certified medication to treat COVID-19. Several drugs that are considered as potentially effective are being used in COVID-19 treatment, many of which are metabolized by CYPs. Of the total CYPs discovered to date, six of these are responsible for 90% of drug metabolism, including CYP1A2, CYP2C9, CYP2C19, CYP2D6, CYP2E1, and CYP3A4 . In thisUpon referring to previous antivirus activity studies, lopinavir–ritonavir was proposed as an emergency treatment in COVID-19 . LopinavRemdesivir is one of few Food and Drug Administration (FDA)-approved treatments for severe cases of COVID-19 . It is mChloroquine and hydroxychloroquine have been suggested as having an antiviral effect in COVID-19 patients, with side effects including arrythmias, cardiovascular complications, hepatological effects, and adverse vision effects . Both ofCorticosteroids are widely used in the treatment of COVID-19 due to their anti-inflammatory and immunosuppressive effects . CorticoThe symptoms of COVID-19 patients are varied, with the most common being fever, cough, digestive tract symptoms, sleep disorders and headaches, which are often treated by medication . IbuprofARDS is a major complication in severe COVID-19 patients, when analgesics and sedatives are routinely used for patients on mechanical ventilation. Fentanyl and morphine are also commonly used for analgesia in patients on mechanical ventilation. Fentanyl and sufentanil are metabolized by CYP3A4 , and hepElderly patients have the highest mortality rate amongst COVID-19 patients, which is generally related to co-existing underlying diseases. Similar to most studies, our previous data showed that the most common comorbidities in this population were hypertension, coronary heart disease, and diabetes . Many drAnti-hypertensive drugs incorporate several classes: diuretics, angiotensin-converting enzyme (ACE) inhibitors, calcium channel blockers (CCBs), angiotensin II receptor blockers (ARBs), and beta-blockers . IndaparAnti-platelet and anti-coagulant drugs are commonly used in the treatment of cardiovascular diseases. CYP2C19, CYP1A2, and CYP2B6 catalyze clopidogrel to the immediate precursor of its pharmacologically active metabolite, whilst CYP3A4, CYP2B6, CYP2C19, and CYP2C9 contribute to the active metabolite formation . CYP2C9 Several oral antidiabetic drugs are also metabolized by CYPs. For example, pioglitazone and rosiglitazone are metabolized mainly by CYP2C8, whilst sulfonylureas are mainly metabolized by CYP2C9; and to a lesser extent by CYP3A4 . RepagliA recent study of 227 hospitalized COVID-19 patients showed that 38% had at least one clinically significant potential drug–drug interaction. More than half of the interactions were between lopinavir/ritonavir and regularly prescribed medications for the management of comorbidities or COVID-19 symptoms . As CYPsAdditionally, traditional Chinese medicine is widely used in the treatment of COVID-19 in China . JingyinThe recent emergence of the COVID-19 pandemic has caused unprecedented global healthcare problems. The most striking pathophysiological feature of COVID-19 is the state of excessive inflammatory response. As the most common drug metabolizing enzyme family, CYPs are closely related to the metabolism of endogenous and exogenous substances. In this review, we analyzed and summarized current evidences regarding the possible changes and roles of CYPs in COVID-19. In COVID-19, viral infection, excessive inflammatory response, and hepatic impairment may all affect CYP expression. CYPs may influence the pathophysiological process of COVID-19 through AA, vitamins, and steroid pathways. Moreover, many of the drugs that are likely to be used in COVID-19 patients are metabolized by CYPs. Since the expression of CYPs may be greatly altered in COVID-19 patients, drug pharmacokinetics may also vary, and drug-related side effects may increase in these patients. In the case of co-administration of multiple drugs, the risk of drug interactions may even increase, and therefore, monitoring of drug concentrations and side effects is essential in this population. Overall, the information on the relationship between COVID-19 pathophysiology and CYPs status, will potentially minimize drug-related toxicity and optimize the treatment of infected individuals.


Human chorionic gonadotropin (hCG) is a glycoprotein hormone secreted by the syncytiotrophoblasts of the placenta. However, hCG (particularly β-hCG) is also expressed in many normal nontrophoblastic tissues. Here, we report the case of a 50-year-old woman diagnosed with ovarian high-grade serous carcinoma with elevated β-hCG, which was insensitive to chemotherapeutic drugs and had a poor prognosis.A 50-year-old woman with abdominal distention was admitted to our hospital. Pelvic computed tomography and magnetic resonance imaging were highly suggestive of multiple metastases of ovarian cancer. Surprisingly, an elevation in β-hCG levels was also measured.The patient underwent laparoscopic examination and was diagnosed with high-grade serous ovarian carcinoma. After 2 prior chemotherapies with paclitaxel and carboplatin, the patient underwent cytoreductive surgery and continued receiving chemotherapy. However, recurrent lesions were observed during the period of chemotherapy, and the level of β-hCG increased. Alternative chemotherapy with liposomal doxorubicin was administered, but it also had a poor therapeutic effect.The progression was rapid with a continuous increase in β-hCG levels, and the patient died 9 months after surgery.Gynecologists should be aware of women with ovarian carcinoma with an elevated β-hCG level, which suggests a poor prognosis. The prognosis of ovarian cancer is the worst among all gynecological cancers. The main reason for this is that approximately 75% of patients are diagnosed at a late stage because of the asymptomatic characteristics at an early stage. Ovarian cancer have a variety of histological subtypes that have different characteristics. Epithelial cancers comprise nearly 90% of all ovarian cancers. Among the above types, high-grade serous carcinoma is the most common type of epithelial ovarian cancer.Ovarian cancer is the tenth most commonly diagnosed cancer and the tenth most common cause of cancer-related deaths among women in China. Furthermore, hCG (particularly β-hCG) has also been expressed in many normal nontrophoblastic tissues, including pituitary glands, testes, prostate, skeletal muscles, and thymus. Recently, it has been demonstrated that elevated β-hCG is ectopically expressed in a large number of malignant tumor tissues, including ovarian, cervical, endometrial, vaginal, breast, bladder, prostate, gastrointestinal, and lung.,5 Here we report the case of a 50-year-old woman diagnosed with ovarian high-grade serous carcinoma with elevated β-hCG, which was insensitive to chemotherapeutic drugs and had a poor prognosis.Human chorionic gonadotropin (hCG), which consists of an α and β subunit, is a glycoprotein hormone secreted by the syncytiotrophoblast of the placenta. The α subunit is structurally similar to luteinizing hormone (LH), while the β subunit is specific for hCG. Similar to LH, hCG binds to LH/hCG receptors (LHCGRs) to regulate reproductive biological processes. However, the presence of LH/hCGRs has also been confirmed in various nongonadal tissues, such as the cervix, uterus, oviduct, breast, adrenal gland, and brain.2FANCA, BRCA1, and BRIP1. Considering that the chemotherapy had poor efficiency, liposomal doxorubicin was administered as an alternative chemotherapy 3 times on February 22, March 22, and April 19, 2019. The values of CA-125 after the 3 alternative chemotherapies were 87.9, 23.8, and 15.1 U/mL while those of HE4 were 113.3, 142.4, and 241.0 pmol/L  was performed, and multiple metastases of the peritoneum and omentum were suspected. Laboratory examination revealed elevated levels of cancer antigen 125 (CA-125) and human epididymis protein 4 (HE4) . Furthermore, a surprising elevation of β-hCG was also found (1315.6 IU/L) on August 31, 2018. Cytology of the ascites exfoliate cells revealed poorly differentiated carcinoma. For further evaluation, she underwent pelvic magnetic resonance imaging and detected massive effusion and enlargement of multiple pelvic and abdominal lymph nodes, as well as abnormal signal intensities in the left adnexa with restricted diffusion on August 31, 2018  is defined as the transformation of aggressive tumor cells to an endothelial cell-like phenotype, thus forming tumor cell-lined vasculature independently, which is independent of host vessels. The presence of VM is highly associated with metastasis and poor prognosis.BCL2, but increased expression of BAX and BIRC5. Furthermore, a low BCL2/BAX ratio was revealed, thus inhibiting apoptosis. Another in vitro study demonstrated that silencing of CGB genes induces apoptosis in cervical cancer cells. The anti-apoptosis effect may be exerted by transforming growth factor β1 in cancer cells. Furthermore, overexpression of hCG promoted the proliferation of ovarian epithelial T29 and T80 cell lines in vitro, as well as increased G2 cell populations and elevated expression of cyclin E, cyclin D1, and cyclin-dependent kinases 2, 4, and 6, thus regulating the progression of the cell cycle.In addition, hCG can also inhibit the apoptosis of cancer cells. It has been reported that overexpression of β-hCG (CGB5 gene) in the ovarian cancer cell lines OVCAR-3 and SKOV-3 showed a remarkable decrease in the expression of  The effect of β-hCG was mediated by the activation of extracellular signal-regulated kinase 1/2 and matrix metalloprotease-2. Overexpression of β-hCG also increased the expression of mesenchymal cell markers and decreased the expression of epithelial cell markers, thus improving EMT and metastasis of ovarian cancer.Epithelial mesenchymal transition (EMT) is defined as polarized epithelial cells that obtain mesenchymal properties that allow them to migrate and invade, which plays an important role in tumor metastasis. During EMT, epithelial cells remodel their cytoskeleton, lose cell–cell junctions, and decrease the expression of epithelial markers such as E-cadherin and zonula occludens-1, leading to increased expression of mesenchymal markers such as N-cadherin, vimentin, and Snail. Overexpression of β-hCG promoted cell migration and invasion in ES-2 and SKOV3 ovarian cancer cell lines by transwell assays and wound healing in vitro and in a nude mouse model in vivo, while silencing β-hCG resulted in the opposite effect.FANCA, BRCA1, and BRIP1, which have been associated with hereditary ovarian cancers. However, the clinical significance of mutations in these genes remains unknown and requires further exploration. Since hCG binds to LHCGRs to regulate biological processes, receptor-mediated therapy might be an alternative for cancer treatment. It has been reported that the effect of hCG-doxorubicin on ovarian cancer cells could increase the activity of doxorubicin and may have better therapeutic effects. However, more effective therapies for cancer with elevated β-hCG levels are imperative.Despite huge progress have been made in the fight against ovarian cancer, great challenges remain for advanced, recurrent, and metastatic ovarian cancer. The gene test of this patient showed mutations of uncertain significance in 4In conclusion, elevated β-hCG levels have been observed in various cancer types in the clinic. HCG has been regarded as a prognostic biomarker that is associated with higher aggressive behaviors. However, the mechanism by which β-hCG affects cancer progression needs to be further explored. Therefore, there is an urgent need to develop more effective anticancer therapies to delay progression and improve prognosis.YZ and YH wrote the manuscript. YJ, TC, and XN contributed to the data collection and analysis. XC and WC contributed to the data interpretation and critical revision. All authors have read and approved the manuscript.Conceptualization: Yi Zhong, Xing Chen.Data curation: Yi Jiang, Ting Chen, Xianglin Nie.Formal analysis: Yi Jiang, Ting Chen, Xianglin Nie.Supervision: Xing Chen, Wenjun Cheng.Writing – original draft: Yi Zhong, Yan Huang.Writing – review & editing: Xing Chen, Wenjun Cheng.


Tetragenococcus halophilus – a halophilic lactic acid bacterium – is frequently used as a starter culture for manufacturing fermented foods. Tetragenococcus is sometimes infected with bacteriophages during fermentation for soy sauce production; however, bacteriophage infection in starter bacteria is one of the major causes of fermentation failure. Here, we obtained whole-genome sequences of the four T. halophilus strains YA5, YA163, YG2, and WJ7 and compared them with 18 previously reported genomes. We elucidated five types of clustered regularly interspaced short palindromic repeat (CRISPR) loci in seven genomes using comparative genomics with a particular focus on CRISPR elements. CRISPR1 was conserved in the four closely related strains 11, YA5, YA163, and YG2, and the spacer sequences were partially retained in each strain, suggesting that partial deletions and accumulation of spacer sequences had occurred independently after divergence of each strain. The host range for typical bacteriophages is narrow and strain-specific thus these accumulation/deletion events may be responsible for differences in resistance to bacteriophages between bacterial strains. Three CRISPR elements, CRISPR1 in strains 11, YA5, YA163, and YG2, CRISPR2 in strain WJ7, and CRISPR2 in strain MJ4, were inserted in almost the same genomic regions, indicating that several independent insertions had occurred in this region. As these elements belong to class 1 type I-C CRISPR group, the results suggested that this site is a hotspot for class 1, type I-C CRISPR loci insertion. Thus, T. halophilus genomes may have acquired strain-specific bacteriophage-resistance through repeated insertion of CRISPR loci and accumulation/deletion events of their spacer sequences. Tetragenococcus halophilus is a halophilic lactic acid bacterium that is abundant in various salted foods such as soy sauce, salted fish, and vegetable pickles  supplemented with 10% NaCl, at 30°C, and under static conditions.1. A de novo assembly of trimmed genome sequences was performed using SPAdes v. 3.13.0  using Mauve v.2.3.1   and the automated QIAcube system (QIAGEN Sciences). Quantity and purity of genomic DNA were assessed using a Qubit 2.0 Fluorometer with a Qubit dsDNA BR Assay Kit  and a NanoDrop 1000 spectrophotometer (Thermo Fisher Scientific). Genomic DNA library was prepared using the Illumina Nextera DNA Flex Library Prep Kit  according to the manufacturer’s instructions. Whole genome sequencing was performed using paired-end sequencing strategy (2 × 300 bp) on an Illumina MiSeq sequencing platform (Illumina). Adapter sequences and low-quality regions were trimmed using Trim Galore! v.0.6.4 with default settings. 3.13.0 . The res v.2.3.1 , 2010. G v.2.3.1 , 2018. T(RefSeq) .The average nucleotide identity based on MUMmer (ANIm) was calculated using the MUMmer 4.0.0 beta2 package . ANIm vacas genes and orientation of CRISPR arrays from genome fragments comprising candidate CRISPR elements were also investigated with CRISPRidentify package  ≥70%. Each orthologous gene set was aligned using MSAProbs v0.9.7 at the amino acid level and was back-translated into nucleotide sequences , which generated 1,686,583, 1,923,062, 1,702,184, and 1,952,698 paired-end reads, respectively. De novo assembly generated high-quality contigs for comparative genomic analyses. The total genome size of these strains ranged from 2,318,625 to 2,443,531 bp with 35.56–35.72% average G + C content. The estimated sequence coverage of the genomes of strains YA5, YA163, YG2, and WJ7 was 414−, 477−, 440−, and 494-fold, respectively. The genome characteristics of the four strains are summarized in 50 values ranged from 41,027 to 44,198 bp. There were 2,400, 2,375, 2,254, and 2,317 protein-coding genes in the genomes of strains YA5, YA163, YG2, and WJ7, respectively. Moreover, 3 rRNA genes, 1 tmRNA gene, and 53–55 tRNA genes were predicted from the four assembled genomes . In contrast, CRISPR1 element in the four strains sequenced in this study showed no transposase in its surrounding regions. This suggests a different insertion pathway of type I-C CRISPR elements. Comparison of two phylogenetically distinct genomes, LMG 26042 and NBRC 12172, which do not possess type I-C CRISPR elements indicated that the dihydroxyacetone kinase operon dhaMKL was conserved in the CRISPR insertion site (data not shown). As this operon was eliminated from all type I-C CRISPR loci inserted genomes, there may be a signal region surrounding this operon for insertion of class 1, type I-C CRISPR loci.elements . HoweverT. halophilus strains showed significant variations in the CRISPR arrays at the genome level. Their accumulated spacer sequences indicate previous encounters with bacteriophages. The distinct CRISPR arrays at almost the same chromosomal location suggest a hotspot for the insertion of CRISPR loci.Comparative genomic studies on these four strains and previously reported 18 T. halophilus. Especially high-frequency insertions occurred in hotspots located at specific chromosomal positions. CRISPR arrays and cas genes are adaptive bacterial immunity systems, particularly regarding anti-phage mechanisms. Evaluating CRISPR elements contributes to identifying robust starter strains and facilitates stable fermentation of industrial-scale soy sauce production. In the future research, we will develop a methodology for rapid detection and classification of CRISPR elements by using PCR-RFLP.We revealed insertion points of nine CRISPR elements in the genome of http://trace.ddbj.nig.ac.jp/BPSearch/bioproject?acc=PRJDB9642.The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found below: DDBJ BioProject MM and AO conceived and designed the study, and performed the experimental procedures. MM analyzed all the data. MM, TW, and AO wrote the original draft of the manuscript. TW, JW, and MT supervised the experimental work, and reviewed and edited the manuscript. All authors approved the final manuscript.TW and JW were employed by the company Yamasa Corporation. The remaining 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.