Mice immunized with 15 μg of VLPs adjuvanted with ISA201 elicited higher levels of E2-specific IgG, IgG1, and IgG2a antibodies as well as higher BVDV-neutralizing activity in comparison with controls. Re-stimulation of the splenocytes collected from mice immunized with VLPs led to significantly increased levels of CD3+CD4+T cells and CD3+CD8+T cells. In addition, the splenocytes showed dramatically enhanced proliferation and the secretion of Th1-associated IFN-γ and Th2-associated IL-4 compared to that of the unstimulated control group. Taken together, our data indicate that BVDV-VLPs efficiently induced BVDV-specific humoral and cellular immune responses in mice, showing a promising potential of developing BVDV-VLP-based vaccines for the prevention of BVDV infections.Bovine viral diarrhea virus (BVDV) is an important animal pathogen that affects cattle. Infections caused by the virus have resulted in substantial economic losses and outbreaks of BVDV are reported globally. Virus-like particles (VLPs) are promising vaccine technology largely due to their safety and strong ability to elicit robust immune responses. In this study, we developed a strategy to generate BVDV-VLPs using a baculovirus expression vector system (BEVS). We were able to assemble BVDV-VLPs composed of dimerized viral proteins E2 and E Bovine viral diarrhea virus (BVDV) is an important pathogen of cattle found in many parts of the world, which poses a great threat to agriculture globally. BVDV is capable of infecting a diverse range of animals, including pigs, sheep, goats, deer, and camelids . Upon inPestivirus in the Flaviviridae family [rns (envelope protein RNase secreted), E1, E2, p7, NS2-3 (NS2 and NS3), NS4A, NS4B, NS5A, and NS5B [BVDV is an enveloped, positively-stranded RNA virus that belongs to the genus e family . BVDV ise family ,6. On the family . The gene family . The fuland NS5B ,10.rns and E2 are highly glycosylated and often exist as homodimers mediated by disulfide bonds. Specifically, Erns contains 8–9 conserved cysteine residues that form intra- and inter-molecular disulfide bonds, more than 50% carbohydrates in the mature form of Erns [rns are the main targets for neutralizing antibodies induced by BVDV infection, making them important subunit antigen candidates for vaccine development. The two surface proteins E of Erns ,12,13,14 of Erns ,16. More of Erns . BVDV’s  of Erns . E2 and Virus-like particles (VLPs) are non-infectious and genome-free virus particles constructed by one or multiple viral proteins. VLPs are similar to infectious virions in structure and conformation, but are non-infectious due to the lack of genetic material. Compared to individual proteins or peptides, VLPs display more repetitive epitopes on the surface, which may trigger stronger B cell and T cell-mediated immune responses ,20.Baculovirus expression vector system (BEVS) has been widely used in the production of VLPs and has been used for the development of several licensed vaccines, such as HPV16/18 vaccine  and influenza virus vaccine  ,22,23. BFlaviviridae family, including dengue fever virus (DENV) [Flaviviridae family. In this study, we generated BVDV-VLPs containing Erns and E2 with BEVS method. We observed the assembly and structure of the VLPs with transmission electron microscopy (TEM) and immune-electron microscopy (IEM). In addition, we immunized BALB/c mice with the BVDV-VLPs we manufactured and evaluated and compared the humoral and cellular immune responses in the animals to that of a commercial BVDV vaccine. Our results suggest BVDV-VLPs generated by BEVS are a promising candidate vaccine for the prevention of BVDV infections.BEVS-based VLPs have been successfully generated for many members of the s (DENV) , Japaness (DENV) , Zika vis (DENV) , West Nis (DENV) , and heps (DENV) . However2.MDBK cells, BVDV 1a strain NADL, were obtained from the China Veterinary Culture Collection Center . Sf9  cells were cultured in suspension in the serum-free Grace medium  supplemented with 1% penicillin–streptomycin  at 27 °C, 100 rpm. MDBK cells were maintained in Dulbecco’s Modified Eagle Medium (DMEM)  supplemented with 10% fetal bovine serum  and 1% penicillin–streptomycin  at 37 °C and 5% COrns proteins (residues 271-497) and E2 proteins (residues 693-1036) were cloned from BVDV 1a NADL (GenBank accession no. AJ133738.1), a gp64 signal peptide sequence (gtaagcgctattgttttatatgtgcttttggcggcggcggcgcattctgcctttgcg) was fused to the N-terminal of Erns or E2 with a Gly-Gly-Gly-Gly-Ser linker, and gp64-Erns and gp64-E2 were cloned into the XhoI-KpnI and BamHI-PstI sites of pFastBac Dual vector . The correct clones were verified via Sanger sequencing and were named pFastBac-Erns+E2, which was transformed into DH10Bac Escherichia coli (E. coli) cells to generate recombinant bacmids rBacmids-Erns+E2. Of the Sf9 cells, 106 were transfected with 1μg rBacmids-Erns+E2 using Cellfectin II  according to the manufacturer’s guidelines. After 5 days, medium from cell culture was collected, centrifuged at 1000× g for 5 min to remove cellular debris, and stored at −80 °C.The coding sequences of the E6 cells/mL were infected with P4 (passage #4) rBac-Erns+E2 with the multiplicity of infection (MOI) of 0.1 for 5 days at 27 °C, and rotated at 100 rpm in a 125 mL culture bottle. Cell suspensions were centrifuged at 1000× g for 5 min to remove supernatant, and the cell pellets were resuspended with 5× volumes of TNE buffer (20 mM Tris-HCl (pH 8.0), 150 mM NaCl, 2 mM EDTA) and sonicated 5 times for 10 s on ice with a sonicator  at 30% amplification. Cell lysates were collected after centrifugation at 12,000 rpm for 20 min and used in the subsequent experiments.Sf9 cells at a density of 3 × 10rns polyclonal antibody (pAb) (prepared by our laboratory) and E2 monoclonal antibodies (mAb) 348 .For VLP purification, the cell lysates were loaded onto gradient sucrose solution  in TNE buffer in a 13.3 mL ultraclear centrifuge tube  and centrifuged at 35,000 rpm, 4 °C for 4 h in an SW41 rotor . Fractions of 1.5 mL were collected dropwise after puncturing the bottom of the tube. The distribution of the VLPs in the gradient was measured by SDS-PAGE  with Coomassie Brilliant Blue staining and Western blot with ESeveral fractions of the sucrose gradient containing the VLPs were mixed with 2× volumes of TNE and centrifuged at 35,000 rpm, 4 °C, for 2 h in an SW41 rotor . VLP pellets were resuspended in 500 μL of TNE and stored at −80 °C.rns pAb and E2 mAb 348 diluted in 5% skim milk in PBST for 1 h at 25 °C, washed 3 times with PBST, and then incubated with HRP-conjugated secondary antibody in 5% skim milk in PBST for 30 min at 25 ℃. Membranes were washed extensively, and signals were detected using the ECL reagents .Purified VLPs or cell lysates were separated by SDS-PAGE under reducing (with 4% β-mercaptoethanol) or non-reducing conditions (without β-mercaptoethanol), and proteins were transferred to PVDF membranes  and blocked for 2 h at room temperature with 5% skim milk in PBST (0.05% Tween in 0.01 M PBS). Blocked membranes were then incubated with primary antibodies Erns+E2 were spun down and resuspended in 2.5% glutaraldehyde, followed by dehydration using a standard graded series of acetone solutions including 50%, 70%, 90%, and 100% for 15 min per step. Cells were then embedded in Epon815 resin  and allowed to polymerize for 24 h at 37 °C, 24 h at 45 °C, and 24 h at 60 °C. Ultrathin sections (70 nm) of these blocks were obtained with a Reichert-Jung Ultracut E ultramicrotome, and sections were deposited on carbon-coated Cu grids and negative stained with 5% uranyl acetate and 5% lead citrate. Specimens were viewed with a JEM-1200EX  transmission electron microscope at 80 kV.Sf9 cells infected by rBac-EFor visualization of the purified VLPs, we applied 20 μL of VLPs onto carbon-coated Cu grids, which were negative stained with 2% uranyl acetate and viewed with the method described above.rns pAb and E2 mAb 348. The 10 nm colloidal gold-conjugated goat anti-rabbit antibody and 5 nm colloidal gold-conjugated goat anti-mouse antibody  were used as the secondary antibody, and subsequently the grids were negatively stained with 2% uranyl acetate and examined with a HT7800  transmission electron microscope at 80 kV.For IEM, 20 μL of VLPs were applied onto carbon-coated Cu grids and blocked with 1% BSA. The primary antibodies were EA total of 48 6–8-week-old female BALB/c mice  were randomly divided into 8 groups (6 per group) and immunized intramuscularly on days 0 and 21 with (I) 5 µg of VLPs, (II) 5 µg of VLPs adjuvanted with 5 µg of ISA201, (III) 10 µg of VLPs, (IV) 10 µg of VLPs adjuvanted with 10 µg of ISA201, (V) 15 µg of VLPs, (VI) 15 µg of VLPs adjuvanted with 15 µg of ISA201, (VII) commercial BVDV inactivated vaccine, and (VIII) TNE and equal volume ISA201.Blood samples were taken through the inner canthal orbital vein for serological analysis on day 42 post-prime immunization, and spleens were harvested from groups (V), (VI), (VII), and (VIII) for flow cytometry and splenocytes proliferation test on day 28 post-prime immunization.E. coli using a pMAL-c5X-His expression vector in CBS  overnight at 4 °C. Next, the plates were blocked with 5% skim milk in PBST (0.05%Tween in 0.01 M PBS) for 2 h at 37 °C. A total of 100 μL of serum samples were diluted 50x times in PBST and added to each well in the plates for 1 h at 37 °C. The plates were then washed 3 times with PBST, and 100 μL of HRP-conjugated goat anti-mice IgG , IgG1  or IgG2a  were 2000-, 4000-, or 500-fold diluted, respectively, in PBST and added to the plates for 1 h at 37 °C. The plates were washed again and 100 μL of TMB  was added to each well prior to adding 50 μL of stopping solution (2 M H2SO4). OD450nm was determined using an ELISA plate reader .BVDV E2-specific serum antibody titers were measured by ELISA. We coated 96-well microtiter plates with 100μL per well of 4μg/mL of purified prokaryotic expressed BVDV-E2 protein produced in 50 was added and samples were incubated for 1 h at 37 °C in a final volume of 200 μL. MDBK cells were infected in triplicate with 100 μL of the neutralization mixture and incubated for 1 h at 37 °C with 5% CO2, the mixture was then removed and replaced with DMEM medium with 2% FBS. Cells were further incubated for 7 days at 37 °C with 5% CO2, and cytopathic effects (CPE) were observed. The 50% neutralization titer of serum was calculated by the Reed and Muench method.The serum samples were heat-inactivated at 56 °C for 30 min and serially diluted twofold in DMEM medium, and then an equal volume of DMEM-diluted BVDV virus containing 100 TCIDg for 30 min. The lymphocyte layer was collected and washed with RPMI 1640 medium, and cell counts were stained with 0.4% trypan blue and counted using the Countess Automated Cell Counter system . Splenocytes were used for subsequent flow cytometry analysis, enzyme-linked immunospot assay (Elispot), and splenocyte proliferation assays. For flow cytometry, splenocytes (5 × 106 cells in 6-well cell culture plates) were stimulated with 10 μg/mL VLPs or inactivated BVDV in the presence of 3 μg/mL Brefeldin A  for 6 h at 37 °C and 5% CO2, and cells were washed using staining buffer  and stained with PE/cyanine7 anti-mice CD3 , PE anti-mice CD4 , and PerCP/cyanine5.5 anti-mice CD8a . Cells were analyzed using BD Fortessa .Spleens were collected from mice on day 28 post-prime immunization and were grounded in a 35 mm Petri dish containing 5 mL of mice 1× lymphocyte separation medium ; suspensions were filtered using 40-μm filters into a new tube and were centrifuged at 800× 6 cells per well) were added to 96-well plates with 1 μg/mL of VLPs or heat-inactivated BVDV, and splenocytes cultured with RPMI 1640 medium alone or 1 μg/mL of ConA  were used as negative and positive controls, respectively. The plates were incubated at 37 °C, 5% CO2, for 72 h. Then, 500 μg/mL of MTT  solution was added to each well and the plates were incubated at 37 °C, 5% CO2, for 4 h. The MTT solution was removed and 150 μL of DMSO was added to dissolve the precipitate at 37 °C for 10 min; the OD570nm was determined using an ELISA plate reader . The stimulation index (SI) was calculated as follows: SI = OD570nm (sample)/OD570nm (blank control).Splenocytes (106 cells per well) were added to anti-mouse IFN-γ or IL-4 monoclonal antibody-precoated ELISpot plates with 10 μg/mL VLPs or inactivated BVDV; splenocytes cultured with RPMI 1640 medium alone or 50 μg/mL PMA/ionomycin were used as negative and positive controls, respectively. The plates were incubated at 37 °C, 5% CO2, for 48 h. Then, the blots were immunostained according to the manufacturer’s instructions and counted using an AID EliSpot Reader . Results are presented as mean number of IFN-γ- or IL-4-secreting cells per 106 splenocytes.Mouse IFN-γ precoated ELISpot kit and Mouse IL-4 precoated ELISpot kit  were used to determine cytokine expression. Splenocytes (10Results are expressed as mean ± standard deviation (SD). Statistical analysis was performed by one-way analysis of variance (ANOVA) with Tukey’s multiple-comparison test in GraphPad Prism.rns and E2; the gp64-Erns and gp64-E2 were then inserted into pFastBac Dual vector to generate the recombinant plasmid pFastBac-Erns+E2 and the subsequent recombinant bacmid rBacmids-Erns+E2. The bacmid was transfected into Sf9 cells and the recombinant baculoviruses rBac-Erns+E2 were rescued using a previously described protocol  and proteins were separated using SDS-PAGE. Expressions of Erns and E2 were examined by Western blot analyses. As shown in rns and E2 proteins were detected in Sf9 cells.The baculovirus gp64 signal peptide was fused to the N-terminal ends of Eprotocol . Sf9 celrns and E2 formed VLPs, we examined ultrathin section of Sf9 cells infected with rBac-Erns+E2 by TEM, as shown in To determine whether Erns+E2 and placed them on top of a sucrose density gradient. Samples were centrifuged at 35,000 rpm for 4 h and then nine fractions (1.5 mL each) were collected from bottom to top. The fractions were next analyzed by SDS-PAGE and total proteins were visualized by Coomassie Brilliant Blue staining. Expression of E2 and Erns were examined by Western blotting analysis. As shown in rns and E2  . The results were compared against the profile of BVDV NADL C. Using rns and E2 concentration using TEM. TEM data showed that the VLPs were spherical in morphology, with diameters of about 50 nm  or nonreducing (NR) conditions and Western blot was performed to determine the expression and multimerization of Erns and E2. As shown in rns, only one predominant band of 48 kDa was detected under reducing condition. As a comparison, only one band migrating at the size of 96 kDa was detectable under non-reducing condition, suggesting the existence of homodimers for both proteins.As native ETo determine the immunogenicity of BVDV-VLPs, we used three doses of VLPs with or without ISA201 adjuvant to immunize BALB/C mice; a commercial BVDV inactivated vaccine and ISA201 adjuvant alone were included as positive and negative controls, respectively. Serum was collected on day 42 post-prime immunization and BVDV E2-specific IgG, IgG1, and IgG2a were examined by ELISA. As shown in To determine if the antibodies elicited by BVDV-VLPs exhibited neutralizing potentials, we collected serum from the vaccinated animals on day 42 post-prime immunization, heat-inactivated the serum at 56 °C for 30 min, and determined their capacity to neutralize BVDV infection in MDBK cells. As shown in +CD4+T cells and CD3+CD8+T cells were analyzed by flow cytometry. As shown in +CD4+T cells and CD3+CD8+T cells were significantly higher in animals treated with VLPs than those treated with the adjuvant alone or the commercial vaccine, suggesting the advantage of BVDV-VLPs in the stimulation of T cell responses over the commercial vaccine.To determine if VLPs could also induce T cell immune responses, we collected mice splenocytes on day 28 post-prime immunization from animals immunized and re-stimulated with 10 μg/mL of VLPs or inactivated BVDV. The abundances of CD3Proliferation of splenocytes upon vaccination signifies a robust activation of the immune responses. To explore the effect of BVDV-VLPs on the proliferation of splenocytes, we harvested splenocytes from immunized mice and performed MTT assay to monitor cell proliferation. As shown in As IL-4 and IFN-γ are major cytokines regulating antibody class switching during BVDV infections, as reported previously, we decided to monitor these two cytokiens following the treatment of VLPs in mice. We chose to monitor Th2-associated IL-4 and Th1-associated IFN-γ in spleen with EliSpot assay. Splenocytes collected from the immunized animals were stimulated with the same antigen as that used for immunization, and the number of IL-4- or IFN-γ-secreting cells were measured and plotted. Remarkably, VLPs were able to trigger improved IL4 and IFN-γ production. In comparison, the commercial vaccine was only able to enhance IFN-γ production up to 50% of the capacity induced by VLPs, and was incapable of inducing any IL-4 production .BVDV is a notorious pathogen in the dairy industry that affects farm animals around the world. In China, the seroprevalence of BVDV in dairy cattle was found to be 57%, and positive rate of viral RNA was estimated at 27.1% according to a meta-analysis performed between 2003 and 2009, and between 2010 and 2018 . An indeCurrently, both inactivated and live attenuated vaccines are commercially available for BVDV. However, drawbacks are associated with both types of vaccines. The attenuated vaccine could harm pregnant cows by causing premature miscarriage, fetal damage, or PI. PI animals are the main source of BVDV transmission. On the other hand, inactivated vaccines are safer for animals but induce a much weaker cellular immune response as compared to the attenuated vaccine. In addition, the vaccinated animals cannot be serologically distinguished from those infected with the wild-type virus, posing a challenge for viral surveillance in the cattle industry. As a result, more efforts are needed to explore the options of safe and effective BVDV vaccines.rns and E2 are the most immunogenic proteins of BVDV and induce high titers of protective neutralizing antibodies after infection; several studies based on vaccination with Erns and E2 glycoprotein expressed in different systems have been reported [rns and E2 need to undergo certain N-linked glycosylation to help them fold correctly [Ereported ,39,40,41reported . As viraorrectly . BEVS harns and E2 proteins using the previously established BEVS method. A comprehensive protein domain analysis by TMHMM suggests that E2 contains an extracellular domain (amino acid residues 693–1036), a transmembrane domain (residues 1037–1059), and an intracellular domain (residues 1060–1066). Erns, on the other hand, does not contain any transmembrane domain. Neither Erns nor E2 contain any signal peptide. Therefore, a signal peptide derived from the baculovirus gp64 surface glycoprotein was fused to the N-termini of Erns and E2 extracellular domains. The baculovirus gp64 signal peptide contains hydrophobic amino acids, which is recognizable by the receptor on the endoplasmic reticulum [rns and E2 enter the ER, assemble into VLPs, and are released from the ER [In this study, we aimed to develop a new type of vaccine by constructing VLPs with viral Eeticulum . The nasm the ER .rns and E2 were clearly visible on the SDS-PAGE gel, and the results of LC–MS/MS confirmed that two protein bands were BVDV Erns and E2 , which is conserved in pestiviruses. A study showed that a mutant classical swine fever virus (CSFV) without C171 is attenuated, indicating the role of dimerization in maintaining its biological function [rns and E2 maintain their natural conformation, which may help maintain their immunogenicity increase specificity of the immune responses from the host.Efunction . In wildrns secretion demands further investigation [Traditionally, VLPs are secretive and are more often purified from cell supernatant than from cell lysates. However, we found only a small portion of VLPs secreted, whereas the majority of them remained intracellularly. Whether modifications on the signal peptides can increase E2/Etigation ,50.After in vitro verification of the VLPs generated, we next assessed the immunogenicity and the neutralization potential of them in BALB/c mice. The results showed that vaccination of mice with BVDV-VLPs induced significantly higher levels of IgG, IgG1, and IgG2a antibodies against BVDV E2 protein compared to controls in the presence of adjuvant A–C. In v+CD4+T cells and CD3+CD8+T cells were enriched upon VLP immunization (In addition to antibody response, we monitored cell-mediated immunity in mice immunized with BVDV-VLPs. We found both CD3nization . Moreovenization . PreviouTaken together, our data suggest that BVDV-VLPs induce strong humoral and cellular immune responses in mice.rns using BEVS. The VLPs produced with this protocol were morphologically and dimensionally similar to the wild-type BVDV particles. In addition, Erns and E2 proteins encapsulated in the VLPs and existed in homodimers, which help preserve the immunogenicity of the two proteins. Furthermore, our BVDV-VLPs were able to induce mice to produce a similar level of humoral immune response and stronger cellular immune response than the commercial BVDV-inactivated vaccine.We successfully established a method to generate BVDV-VLPs with viral E2 and E


This work aims to analyze the 100 most cited papers in radiotherapy or chemoradiotherapy for cervical cancer.The 100 most cited papers in radiotherapy or chemoradiotherapy between 1990 and 2020 were identified with Thompson Reuters Web of Science citation indexing on August 24, 2020. The publication years, source titles, countries/regions, total citations, and average citations per year were extracted from the Web of Science. The research type and research domain were classified by the authors.These 100 papers were cited a total of 28,714 times, and the median number of citations was 169.5 . The most cited paper was “Concurrent cisplatin-based radiotherapy and chemotherapy for locally advanced cervical cancer” by Rose et al., with a total citation of 1,700 times. The International Journal of Radiation Oncology Biology Physics (40 papers), Radiotherapy and Oncology (14 papers), and the Journal of Clinical Oncology (12 papers) published the largest number of papers. USA (47 papers), Austria (18 papers), Canada (13 papers), and England (13 papers) contributed the largest number of papers. Image-guided adaptive brachytherapy (IGABT) had the largest number of papers (25 papers). Concurrent chemotherapy was the most cited research domain, with 10,663 total citations and 592.4 citations per paper.In the present study, we conducted a bibliometric analysis of the 100 most cited papers in radiotherapy or concurrent chemoradiotherapy for cervical cancer in the past 30 years. IGABT and concurrent chemotherapy were the most cited research domains. Cervical cancer is one of the most common cancers globally, especially in countries with a middle/low human development index . RadiothIt is a challenging task for researchers to identify the most influential work in a specific area. Bibliometric analysis, also known as citation analysis, is one way to identify the most influential papers. The citation frequency of a paper can reflect its impact. In the present study, we performed a bibliometric analysis of the 100 most cited papers in radiotherapy or chemoradiotherapy for cervical cancer to identify the most influential work in this area.The Thompson Reuters Web of Science citation indexing database was used to identify the most cited papers. The bibliometric analysis was performed on August 24, 2020. The database selected was the Web of Science Core Collection. The time span was 1990–2020. No restriction was placed on the language or document types. The search strategy was as follows: Title =  AND Title = (brachytherap* OR chemoradi* OR chemo-radiotherap* OR dosimetric OR EBRT OR DVH OR fractionat* OR IGABT OR IGART OR IGRT OR IMRT OR irradiation OR multileaf OR proton-beam OR proton-therapy OR radiation OR radiosurgery OR radiother* OR SBRT OR Tomotherapy OR VMAT). The search results were ranked by the number of times the papers were cited to identify the 100 most cited papers.The publication years, source titles, and countries/regions of the 100 most cited papers were collected with “Analyze Results” from the Web of Science. The total citations and average citations per year were extracted with “Create Citation Report” from the Web of Science.versus observations after hysterectomy, definitive radiotherapy versus surgery, and others.Research types and research domains were classified independently by two authors, WW and DW. Discrepancies were resolved by the third author XL. Research types were classified into research articles, guidelines (including recommendations and consensus), reviews, meta-analyses, editorials, and letters. Research domains were classified into brachytherapy (including IGABT and non-IGABT), external beam radiation therapy (including IMRT and extended-field irradiation), chemotherapy (including concurrent chemotherapy and neoadjuvant/adjuvant chemotherapy), radiosensitivity and biomarkers associated with the efficacy of radiation therapy, prognostic factors of survival after radiation therapy, adjuvant radiotherapy There were 6,218 papers that fulfilled the criterion described above. The 100 most cited papers were identified, and they are listed in These most cited 100 papers were published between 1990 and 2016. The publication time distribution is shown in Among these papers, there were 83 research articles, 10 guidelines, recommendations, or consensuses, six meta-analyses, and one editorial. Of the 83 research articles, 20 were randomized clinical trials (RCTs). The average citations per paper of RCTs, meta-analysis, and non-RCT research articles were 584.8, 357.7, and 180.5, respectively.As shown in A total of 36 countries or regions participated in the publication of the 100 most cited papers. Most of them are developed countries. As shown in The research domains of these papers are shown in In the subdivided research domains, IGABT had the largest number of papers (25 papers). Concurrent chemotherapy was the most cited research domain, with 10,663 total citations and 592.4 citations per paper.The main research domain in different time periods is shown in All of the 18 papers on concurrent chemotherapy were published between 1998 and 2010. Of them, there were 11 RCTs, six meta-analyses, and one editorial. Eight of them were published in the Journal of Clinical Oncology, followed by the New England Journal of Medicine (four papers) and the Cochrane Database of Systematic Reviews (two papers). The USA participated in 10 of these papers, followed by Canada (five papers), England (four papers), and Thailand (two papers).All 25 papers on IGABT were published between 2003 and 2016. Of them, 11 papers were published in the International Journal of Radiation Oncology Biology Physics, 11 papers were published in Radiation and Oncology, two papers were published in Brachytherapy, and one paper was published in Acta Oncology. Austria participated in 17 of these papers, which was the most, followed by France (seven papers), Denmark (six papers), the USA (six papers), and Belgium (five papers).versus single radiotherapy was 10,663, which was the largest. Before 1999, single radiotherapy or radiotherapy combined with hydroxyurea was performed for cervical cancer. Between 1999 and 2000, five randomized clinical trials demonstrated that cisplatin-based CCRT was superior to radiotherapy  GEC ESTRO Working Group , 16, 17 IMRT is an important technical advancement in radiotherapy. Compared with conventional or conformal radiotherapy, for cervical cancer, IMRT is superior in sparing the bowel, rectum, and bladder , 24 ran ranked . The Radetc. Immunotherapy and targeted therapy are also potential ways to prevent distant metastasis of LACC in the future.We identified hotspots in the area of radiotherapy or chemoradiotherapy in cervical cancer using the 100 most cited papers. CCRT and adjuvant radiotherapy improved the survival of patients with cervical cancer. IGABT and IMRT reduce the toxicity of radiotherapy. The local control of LACC is excellent with CCRT, IGABT, and IMRT , 35. At This study has some limitations. First, the citations of papers are influenced by many factors, including types of papers, journals, publication time, influence of authors, and even social media exposure. The citation of papers was influenced by the time span after publication. As a result, eight of the 10 most cited papers were published before 2001, and 83 of the 100 most cited papers were published before 2009. No papers published after 2017 were ranked among the top 100 papers. This may lead to missing impactful studies published in the past few years. The number of citations per year was used in the present study to balance the impact of the time span after publication on the selected papers. Second, some highly cited papers are not applicable or insignificant at present. For example, in 1990, Soisson et al. conducted a nonrandomized study that demonstrated that adjuvant radiotherapy following radical hysterectomy had limited benefit for patients with stage IB and IIA cervical cancer compared with radical hysterectomy alone   and the National Key Technologies Research and Development Program of China (grant number 2016YFC0105207).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.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


While shaped and constrained by axonal connections, fMRI-based functional connectivity reorganizes in response to varying interareal input or pathological perturbations. However, the causal contribution of regional brain activity to whole-brain fMRI network organization remains unclear. Here we combine neural manipulations, resting-state fMRI and in vivo electrophysiology to probe how inactivation of a cortical node causally affects brain-wide fMRI coupling in the mouse. We find that chronic inhibition of the medial prefrontal cortex (PFC) via overexpression of a potassium channel increases fMRI connectivity between the inhibited area and its direct thalamo-cortical targets. Acute chemogenetic inhibition of the PFC produces analogous patterns of fMRI overconnectivity. Using in vivo electrophysiology, we find that chemogenetic inhibition of the PFC enhances low frequency (0.1–4 Hz) oscillatory power via suppression of neural firing not phase-locked to slow rhythms, resulting in increased slow and δ band coherence between areas that exhibit fMRI overconnectivity. These results provide causal evidence that cortical inactivation can counterintuitively increase fMRI connectivity via enhanced, less-localized slow oscillatory processes. Pathological perturbation affects whole brain network activity. Here the authors show in mice that cortical inactivation unexpectedly results in increased fMRI connectivity between the manipulated regions and its direct axonal targets. The non-invasive nature of rsfMRI has fueled the use of this method to map intrinsic brain network organization in the healthy human brain, as well as in psychiatric or neurological conditions, in which evidence of disrupted or aberrant rsfMRI functional coupling has been largely documented1. However, despite the growing popularity of rsfMRI, our knowledge of the underpinnings of brain-wide fMRI coupling remains very limited.A rapidly expanding approach to understand the functional organization of brain networks is to map large-scale patterns of spontaneous activity via non-invasive neuroimaging. The ease and reproducibility of “resting state” fMRI (rsfMRI) have promoted the widespread use of this approach, leading to the observation that spontaneous fMRI activity is organized into highly coherent functional networks, defined by temporally correlated fluctuations in BOLD signal1. First, structural and functional connection strengths are correlated both at the whole-brain and mesoscopic scale4, and rsfMRI network topography closely recapitulates patterns of anatomical connectivity in several mammalian species6. Second, experimental resection of callosal connections7 or chemogenetic inactivation of the amygdala results in reduced rsfMRI connectivity with regions anatomically linked to the manipulated area8. Lastly, computational modeling corroborates a tight relationship between structural and functional connectivity, as synchronous rsfMRI fluctuations can be modeled by dynamical systems endowed with realistic anatomical connectivity patterns of long-range axonal interactions9. Accordingly, simulated axonal lesions in these models result in reduced functional coupling10.Multiple lines of evidence suggest that structural and rsfMRI-based connectivity are robustly related1. However, the neural mechanisms linking regional brain activity to large-scale rsfMRI network connectivity remain unclear. For example, growing experimental evidence suggests that, while tightly constrained by underlying anatomy, rsfMRI connectivity may only partially reflect direct interactions between areas, as widespread BOLD signal modulation might arise via subcortical connections, whether through the thalamus via long-range loops11, or as a result of diffuse neuromodulation mediated by brainstem nuclei13. This notion is epitomized by the observation of intact rsfMRI coupling among brain regions not directly structurally connected as in the case of acallosal humans, primates, and rodents15. Moreover, rsfMRI network topography can dynamically reconfigure in response to local perturbations16 or pathological processes17. In keeping with this, neurological disorders such as Parkinson’s disease, stroke, and Alzheimer’s disease have been often found to be associated with unexpectedly increased interareal rsfMRI connectivity despite the loss of cortical function characterizing these conditions19. Taken together, these observations point at a complex relationship between interareal brain activity and rsfMRI coupling, and call for a deeper investigation of the neural mechanisms underlying the reconfiguration of rsfMRI connectivity in response to varying interareal input or pathological perturbations.These observations have prompted the widespread use of statistical dependencies in spontaneous fMRI signal as an index of interareal functional communication20), and in vivo electrophysiology in the mouse to probe how inactivation of a cortical area causally affects rsfMRI coupling. Surprisingly, we find that chronic and acute inhibition of the medial prefrontal cortex (PFC), a core component of the mouse default mode network DMN21, can increase rsfMRI coupling with its thalamo-cortical targets. This effect is associated with decreased ϒ power in the suppressed region and robustly increased low frequency (0.1–4 Hz) electrophysiological coherence between functionally overconnected PFC targets. These findings reveal a highly dynamic, non-monotonic relationship between regional cortical activity and network-wide rsfMRI connectivity, and provide an interpretative framework for the observation of counterintuitively increased rsfMRI connectivity in pathological conditions characterized by impaired cortical function.Here we combine rsfMRI, neural and chemogenetic inhibition . Importantly, all the thalamic and cortical regions showing increased rsfMRI connectivity in Kir2.1 mice are characterized by high axonal projection density from the PFC, as seen by comparing the magnitude of inter-group rsfMRI connectivity differences with incoming axonal connectivity strength inferred from a voxel-model of the mouse brain connectome4 . Interestingly, the direction and anatomical location of DMN rsfMRI overconnectivity was not altered by global fMRI signal regression  and hM4Di-expressing animals underwent rsfMRI scanning or electrophysiological recordings before and after intravenous injection of the DREADD activator clozapine-N-oxide (CNO). To account for the relatively slow pharmacokinetic profile of CNO in the rodent brain30, both imaging and electrophysiological recordings were split into a pre-CNO injection baseline, a transitory (0–15 min) drug-equilibration period, and an active time window (15–50 min post CNO injection) to which all our analyses refer to, unless otherwise specified . As expected, CNO administration robustly inhibited firing rate in hM4Di expressing mice, but not in control subjects . DREADD-induced PFC inhibition was characterized by a gradual decrease of neural firing upon CNO administration, reaching a steady-state ~10–15 min after the intravenous bolus . Notably, the direction and the anatomical location of the observed rsfMRI overconnectivity was regionally unaltered by global fMRI signal regression , and overconnectivity gradually emerged in the hM4Di cohort after CNO administration, peaking during the DREADD active time-window  nor were between-group differences in arterial blood pressure  or blood gas levels observed . These control measurements rule out major spurious vascular or hemodynamic contributions and corroborate the specificity of the mapped changes. Importantly, a replication of our chemo-fMRI study in a new set of animals imaged using a combination of medetomidine and low-dose isoflurane36 revealed increased rsfMRI coupling between PFC and thalamic and retrosplenial areas  versus more unimodal lateral portions of the thalamus, we used k-means (k = 1–3) and hierarchical clustering to partition thalamic voxels based on their whole-brain rsfMRI connectivity profile38. Consistent with the neuroanatomical organization of this region, our approach revealed two segregable thalamic sub-territories, one encompassing its centromedial and anterodorsal (PFC-innervated) polymodal components, and the second encompassing more lateral  areas . Given that higher LFP frequencies typically reflect local neural interactions, while lower LFP frequencies are instead associated with larger-scale phenomena42, these results suggest that chemogenetic inhibition of PFC suppresses local, rather than global, neural processes.To obtain insight into the neural rhythms underlying the observed rsfMRI overconnectivity, we next analyzed local field potential (LFP) traces obtained from the same set of PFC electrophysiological recordings analyzed in Fig. To investigate the relationship between DREADD-induced reduction in firing and the concomitant increase in local slow and δ oscillatory power, we next performed phase locking analyses of MUA firing in the PFC. Interestingly, our investigations revealed that in DREADD-expressing animals, the fewer residual spikes recorded after CNO injection exhibited strong phase locking to ongoing slow and δ LFP oscillations. Such strong phase locking was not observed in control animals or in baseline recordings, where spike distributions were instead more equally spread across δ and slow oscillation phases Fig. . These oTo better illustrate the relationship between increased oscillation power and enhanced spike locking in the slow and δ bands, we performed a simple simulation. Specifically, we first simulated spike trains to have weak phase locking to a slow rhythm, with spikes happening almost equally across phase angles of the oscillatory cycle as observed in control conditions. To mimic DREADD-induced effects, we next selectively removed spikes emitted at the non-preferred phases of slow oscillatory activity as observed in our recordings. To mimic DREADD-induced effects, we next selectively removed spikes emitted at the non-preferred phases of slow oscillatory activity as observed in our recordings. In keeping with our experimental results, this simple simulation showed that the removal of “asynchronous” off-preferred-phase firing reduces power of high-frequency spiking activity, while simultaneously increasing the power of the low-frequency rhythm residual spikes are entrained to Fig. . This suFinally, to further probe the mechanistic specificity of our findings, we measured rsfMRI connectivity profiles produced by cell-type-specific manipulations designed to increase local PFC firing. We found that chemogenetic inhibition of fast-spiking Parvalbumin (PV) GABAergic cells or hM3Dq-based excitation of pyramidal (CamkII-expressing) neurons both produced PFC underconnectivity with cortical terminals of the DMN Fig. . Notably45. To test this hypothesis, we carried out a new set of simultaneous multi-electrode LFP recordings in the PFC, retrosplenial, and centromedial  thalamus of control and DREADD-transfected animals . We next computed inter-areal coherence between the envelope of ϒ-band amplitude because ultra-slow (~0.1 Hz) variation in ϒ-band envelope has been linked to arteriole dynamics and suggested to be a contributing factor to rsfMRI coupling46. Mean coherence plots of ϒ-envelope over the ultra-slow frequency range (0.02–0.5 Hz46) revealed only marginally increased CNO-induced coherence in hM4Di expressing mice  interareal rsfMRI connectivity in hM4Di and control animals . Only δ LFP coupling however retained a significant correlation with rsfMRI connectivity upon FDR correction . A much weaker correlation between band-specific LFP coherence and pairwise rsfMRI connectivity was apparent for all the other bands . These findings were paralleled by the observation of similarly robust increased interareal δ- and slow-band LFP phase coherence, a widely used measure of functional synchronization in LFP/EEG studies48  to the establishment of interareal rsfMRI coupling. This view is in keeping with correlational evidence of a dissociation between rsfMRI connectivity and underlying anatomical connections, such in the case of acallosal brains in which preserved bi-hemispheric connectivity has been repeatedly observed15. It should be emphasized here that these results should not be intended as a refutation of the structural foundations of rsfMRI connectivity, but rather the basis of an updated framework in which reciprocal interareal rsfMRI coupling can be strongly biased, or even overridden, by slow synchronized input from global rhythm generators.Our results advance our understanding of the principles underlying brain-wide rsfMRI coupling in two directions. First, we provide causal evidence that regional suppressions of brain activity does not necessarily lead to reduced neural and functional coupling between the inactivated area and its direct anatomical projection targets, but can result in increased rsfMRI connectivity via enhanced, less-localized slow oscillatory coherence. These observations point at a highly dynamic and non-monotonic relationship between structural and functional connectivity, underscoring a critical contribution of remote sources of large-scale neural covariation  play a role in the observed overconnectivity, and the identification of neural generators of rsfMRI coupling and their involvement in the reconfiguration of rsfMRI topography in response to local perturbations remain an open issue.Second, our results also provide an updated reference framework for the interpretation and reverse engineering of rsfMRI overconnectivity observed in brain pathology, especially in degenerative or neurological states characterized by rsfMRI overconnectivity. While a neural mass phenomenon like interareal rsfMRI coupling cannot be mechanistically dissected into discrete circuital elements, our observation of foci of overconnectivity in polymodal thalamic areas and the increased synchronization of these with larger cortical territories is intriguing, as it points at a putative involvement of higher order thalamic relay in the generation (or propagation) of the observed overconnectivity. This hypothesis would be consistent with the observation that full expression of δ and slow oscillatory activity requires thalamic participation59. Our findings corroborate and expand these investigations by showing that reconfiguration of rsfMRI connectivity in response to local cortical inactivation is supported by increased interareal slow oscillatory coherence, a phenomenon reflecting DREADD-induced reduction of high-frequency firing, and concomitantly increased phase locking of residual spiking activity with ongoing global low-frequency oscillations. Recent work has linked ultra-slow (~0.1 Hz) variation in gamma-band amplitude to the vasomotor activity underlying intrinsic rsfMRI connectivity46, suggesting that this rhythm may serve as a possible primary generator of interareal rsfMRI coupling. Interestingly, while we found evidence of ultra-slow ϒ envelope coherence across functionally connected areas under basal conditions  of the primary motor cortex62. Analgously increased rsfMRI overconnectivity and δ hyper-synchronization have also been observed patients with stroke and in early stage Alzheimer’s disease imaged in conscious conditions65. Given the highly dynamic nature of rsfMRI network activity, the sign and neurophysiological signatures identified in this study could however conceivably be affected by arousal levels. In this respect, a recent report of rsfMRI underconnectivity after chemogenetic inhibition of the rat postero-dorsal cingulate cortex is of interest in the light of a possible high-arousal state of these awake, restrained animals66. While the lack of electrophysiological recordings in this study prevents a direct comparison with our findings, high-arousal conditions are characterized by a robust shift towards high-frequency LFP activity and a possibly dominant contribution of direct feedforward interactions to interareal communication. Under these conditions, the synchronizing contribution of slow oscillatory activity may thus be largely reduced, and chemogenetic inhibition could thus produce qualitatively different effects. As robust methods for mapping rsfMRI activity in awake mice are becoming available67, systematic investigations of the effect of DREADD inhibition as a function of arousal state may help probe the plausibility of this model.Although the light sedation protocol used in our measurements enhances slow oscillatory rhythms61 also show that excitatory pulse stimulations may produce rsfMRI de-synchronization, pointing at a possible general, inverse relationship between local cortical activity and interareal rsfMRI coupling. An analogous relationship might also be present in the mouse because, reconstituting the results of our control experiments, decreased rsfMRI connectivity has been recently observed with excitatory DREADD stimulation of somato-motor areas in lightly anesthetized animals68. This relationship however requires further corroboration, as KORD-based chemogenetic inhibition of the cingulate cortex was instead reported by others to produce rsfMRI underconnectivity in anesthetized mice69. These inconsistencies reveal the critical need to couple perturbational rsfMRI studies with electrophysiological recordings to confirm the effect of the designated manipulation, and relate changes in rsfMRI connectivity to underlying neural rhythms.Interestingly, TMS investigations27, an effect that in the case of chemogenetics might also be compounded by possible off-target effects of commonly used chemogenetic actuators70. By employing unlike others69, a design in which CNO is administered under all conditions to all experimental groups, we were able to rigorously control any confounding effect of this actuator via a direct contrast of CNO-treated control and DREADD-expressing animals. As a result, the effects we report in the manuscript are to be attributed to the sole DREADD activation. The observation that chronic inhibition with Kir2.1 reconstitutes the overconnectivity obtained under DREADD manipulation increases our confidence in the validity of our mechanistic inferences. Second, it should be emphasized that the mechanisms that we report here may not be necessarily applicable to awake, behaving conditions, as task-dependent cognitive and sensory processing may strongly and dynamically bias brain rhythms and interregional coupling beyond what could be inferred in the resting, sedated brain. This aspect however does not diminish the translational impact of our findings, owing to the prominent use of resting-state fMRI to map functional network activity and our current inability to back-translate rsfMRI signatures of brain dysfunction into physiologically interpretable events.A strength of our approach is the use of translationally-relevant fMRI-based readouts enabling a possible extrapolation of experimental findings to analogous human research. However, some limitations need to be recognized when assessing the generalizability of our results across species and conditions. First, the magnitude and direction of rsfMRI connectivity produced by neuronal inhibition could be manipulation specificIn conclusion, the present work provides causal evidence that inhibition of a cortical region can lead to counterintuitively increased patterns of rsfMRI connectivity, an effect mediated by increased interareal slow-frequency coherence. These findings point at a non-monotonic relationship between regional cortical activity and network-wide rsfMRI connectivity, and define testable network-level mechanisms for the emergence of rsfMRI overconnectivity in clinical conditions characterized by loss of cortical function.All in vivo experiments were conducted in accordance with the Italian law . Animal research protocols were reviewed and consented by the animal care committee of the University of Trento and Italian Ministry of Health (authorization no. 852/17 to A.G.). All surgical procedures were performed under anesthesia.tm1(cre)Arbr/J, Jackson laboratories, Stock No 017320)71. Mice were group housed in a 12:12 h light-dark cycle in individually ventilated cages with access to food and water ad libitum and with temperature maintained at 21 ± 1 °C and humidity at 60 ± 10%.Kir 2.1, hSyn-hM4Di inhibition and CamkII-hM3Dq stimulation studies were carried out in adult (6 week old) male C57Bl6/J mice . hM4Di inhibition of parvalbumin-positive neurons was carried out in adult (6 week old) transgenic animals expressing Cre recombinase in parvalbumin-positive GABAergic neurons , the anterior cingulate cortex, corresponding to Brodmann area A24b, and the infralimbic cortex, corresponding to Brodmann area A24a. Our viral manipulations were therefore aimed to inhibit an anatomical ensemble comprising all the abovementioned regions at the following coordinates, expressed in millimeter from Bregma: 1.7 from anterior to posterior, ±0.3 lateral, −1.7 deep74.Our anatomical definition of mouse medial prefrontal cortex (PFC) reflects recent neuroanatomical28, all in vivo viral transductions were carried out using high-titer (>1013 vg/mL) viral suspensions. The following injections volumes were employed: 300 nL (AAV8-hSyn-hM4D(Gi)-mCherry and AAV8-hSyn-GFP; http://www.addgene.org) or 2 μL (AAV8-hSyn-MYC-mKir2.1(E224G/Y242F)-IRES-GFP, Xue et al.23, http://www.vectorbiolabs.com or AAV8-hSyn-GFP http://www.addgene.org), or 1 μL (AAV8-CamkII-hM3D(Gq)-mCherry; http://www.addgene.org) or 300 nL (AAV9-hSyn-DIO-hM4D(Gi)-mCherry; http://www.addgene.org) of viral suspension were injected bilaterally in the mouse PFC (see coordinates above). Control groups for both CamkII-hM3D(Gq) and PV-hM4D(Gi) were obtained by sham-injecting genotype-matched littermates. rsfMRI or electrophysiological recordings were carried out no sooner than three weeks after the injection to allow for maximal viral expression.Mice were anesthetized with isoflurane and head-fixed in a stereotaxic apparatus (Stoelting). Injections were performed with a Hamilton syringe mounted on Nanoliter Syringe Pump with controller (KD Scientific), at a speed of 0.05  μl/min, followed by a 5–10 min waiting period, to avoid backflow of viral solution. To prevent layer- or cell-type-specific expression76. Briefly, mice were anesthetized with isoflurane , intubated, and artificially ventilated . The left femoral artery was cannulated for continuous blood pressure monitoring. At the end of surgery, isoflurane was discontinued and substituted with a shallow halothane regimen (0.75%) to obtain light sedation and to preserve cerebral blood flow auto-regulation77. Ventilation parameters were adjusted to maintain normo-physiological paCO2 (<40 mmHg) and paO2 levels . To probe the generalizability of our findings, we also repeated our inhibitory chemo-fMRI manipulations under a combination of medetomidine and low-dose isoflurane .The animal preparation protocol was recently described in great detail78. The scanner was operated using Paravision 6.01 software . Single-shot BOLD rsfMRI time series were acquired using an EPI sequence with the following parameters: TR/TE 1000/15 ms, flip angle 60°, matrix 98 × 98, FOV 2.3 × 2.3 cm, 18 coronal slices, slice thickness 550 µm, bandwidth 250 KHz. rsfMRI acquisition with Kir2.1-transduced (AAV8-hSyn-MYC-mKir2.1(E224G/Y242F)-IRES-GFP, n = 16) and control mice  encompassed 35-min-long timeseries, corresponding to 2100 volumes.rsfMRI data acquisition commenced 30 min after isoflurane cessation. Functional images were acquired with a 7 T MRI scanner  equipped with a BGA-9 gradient set , using a 72 mm birdcage transmit coil and a 4-channel solenoid coil for signal reception30. All group comparisons in the chemo-fMRI study were carried out within this latter time window, unless otherwise stated. After post-mortem analyses of viral expressions, a total of n = 15 hM4Di and n = 19 GFP-transduced animals were retained for analyses.Chemo-fMRI acquisitions comprised two consecutive rsfMRI timeseries, encompassing 1800 volumes (30 min) and 2100 volumes (35 min), respectively. CNO  was injected intravenously fifteen minutes (volume #900) after the start of the first scan. The first 900 fMRI volumes of this first timeseries scan were used as pre-CNO baseline rsfMRI reference in time-resolved analyses. Based on the pharmacokinetic profile of CNO, the post CNO window was split into temporal domains as follows: the first 15 min post injection (900 volumes) were considered part of a drug equilibration window, while the following 35 min (2100 volumes) were considered to cover the DREADD active time window75. Motion traces of head realignment parameters (3 translations + 3 rotations) and mean ventricular signal  were used as nuisance covariates and regressed out from each time course. All rsfMRI time series also underwent band‐pass filtering within a frequency window of 0.01–0.1 Hz  or 0.01–0.25 Hz MED-ISO35, followed by spatial smoothing with a full width at half maximum of 0.6 mm. To control for the effects of global fMRI signal regression on the mapped changes, all rsfMRI timeseries were also recomputed by regressing average fMRI signal within an intracerebral mask.Raw rsfMRI timeseries were preprocessed as follows. The initial 120 volumes of the time series were removed to allow for thermal gradient equilibration. Data were then despiked, motion corrected, and spatially registered to a common reference templatet test  and family‐wise error (FWE) cluster‐corrected using a cluster threshold of p = 0.050 as implemented in FSL (https://fsl.fmrib.ox.ac.uk/fsl/). The antero‐posterior connectivity profile of the DMN was assessed by computing Person correlation between the PFC seed abovementioned and a series of 6 × 6 × 2 voxel seeds placed along the midline extension of the cingulate and retrosplenial cortices26. Quantification of cortico-thalamic connectivity was carried out with respect to a meta-regional parcellation of the mouse cortex in volumes-of-interest. To rule out a possible confounding contribution of spurious neurovascular changes in CNO-induced rsfMRI connectivity alterations, we calculated and statistically compared the characteristic hemodynamic response function79 between Kir2.1 and control mice, and between hM4Di-expressing and control mice upon CNO-administration (active phase).rsfMRI connectivity of the mouse DMN in Kir2.1 and chemo-fMRI scans was probed using a seed-based approach. In the case of the chemo-fMRI study, this quantification was carried out during the CNO active time window. A 5x5x2 seed region was selected to cover the PFC areas targeted by viral injections. Voxel‐wise intergroup differences in seed-based mapping were assessed using a 2‐tailed Student’s 78: TH: thalamus ; STR: striatum ; LCN: lateral cortical network ; HCP: hippocampus ; DMN: default mode network ;Whole-brain connectivity in hM4Di and Control mice was calculated across a set of volumes of interest recapitulating anatomical areas of the Allen brain atlas. The anatomical probed area were selected according to their coverage of previously characterized network systems of the mouse brain3) version of a voxel scale model of the Allen Brain Institute structural connectome4. We then plotted the strength of PFC-departing structural projections against the corresponding between-group difference in rsfMRI connectivity using the cluster-corrected difference map and assessed differences in the distribution of overconnected areas with respect to all the brain voxels using a Wilcoxon rank-sum test.To relate the strength of underlying anatomical connectivity to the regions exhibiting increased rsfMRI connectivity with voxel resolution, we extracted outgoing projections from the affected PFC regions using a spatially-resampled , intubated, artificially ventilated (2% maintenance), and head-fixed in a stereotaxic apparatus (Stoelting). The tail vein was cannulated for CNO injection. To ensure maximal consistency between viral injections and recording site, the skull surface was exposed and an insertion hole in the right PFC was gently drilled through the skull corresponding to the location of prior viral injection point. A single shank electrode  was next inserted through the overlying dura mater by a microdrive array system  at an insertion rate of 1 µm/min to reach the same stereotaxic coordinates employed for viral injection. The site receptive fields were plotted manually and the position and size of each field were stored together with the acquisition data. After electrode insertion, isoflurane was discontinued and replaced by halothane at a maintenance level of 0.75% to induce rsfMRI-comparable sedation. Electrophysiological data acquisition commenced 1 h after isoflurane cessation. Such transition time was required to ensure complete washout of isoflurane anesthesia and avoid residual burst-suppressing activity associated with extended exposure to deep anesthetic levels.Electrophysiological recordings were carried out in animals subjected to the same animal preparation and sedation regime employed for rsfMRI mappingn = 5 hM4Di and n = 5 GFP-expressing mice. Signals were amplified using an RHD 2000 amplifier system  to acquire electrophysiological data at a sampling rate of 20 kHz. For CamkII-hM3D(Gq) (n = 4) and PV-hM4D(Gi) (n = 6) experiments we acquired respectively n = 4 and n = 7 control animals. In the case of control Kir2.1 recordings, a four shank electrode was inserted along the coronal plane to bi-hemispherically cover the right (Kir2.1-expressing) and left (GFP-expressing) PFC (n = 4). The left region served as internal reference control to better assess the efficacy of Kir2.1 neural inhibition. Electrophysiological signals were then recorded into 5 min time bins to cover a 35-min time-window.Neural activity was next recorded in consecutive 5 min time bins to cover a 15 min pre-injection time window, and a 60 min post CNO timeframe in n = 4 hM4Di and n = 5 GFP-expressing mice. A multi-probe micromanipulator  was used to insert three 16 channels single shank electrode  in the right prefrontal cortex, centromedial thalamus, and retrosplenial cortex, respectively. Representative electrode locations are reported in Fig. To measure multi-electrode coherence, three electrodes were inserted in key cortical and subcortical substrates identified as overconnected in our chemo-fMRI mapping in 82. Briefly, raw timeseries were first low-pass filtered using a 4th order Butterworth filter with a cut-off frequency of 1 kHz. The resulting timeseries were next down-sampled to 2 kHz, then again filtered using a Kaiser window filter between 1 Hz to 250 Hz  and then resampled at 1 kHz. All the filtering was applied both in forward and backward temporal direction to avoid any phase transitions due to filtering.To compute the LFP signal, raw extracellular recordings were first down-sampled to 4 kHz, then band-pass filtered to 1–250 Hz using a two-step procedure82. Briefly, we computed a band-passed high-frequency signal using a 4th order Butterworth filter with a <100 Hz cut off frequency, then band-pass filtered between 400 and 3000 Hz using a Kaiser window filter . From the high-frequency signal we detected spike times using a spike detection threshold corresponding to 4-times the median of the high-frequency signal, then divided by 0.6745 as suggested in Quiroga et al. (2004). Spikes were considered to be biologically plausible, and as such retained in these computations, only if occurring more than 1 ms apart.To compute multi-unity activity (MUA) we again followed the procedure described in ref. .1 in suppressing spontaneous activity, firing rate was computed (in units of spikes/s) by dividing the number of spikes per electrode by the recording duration in seconds. The resulting spike rates were averaged across the channels corresponding to the virally targeted or control region. The average spike rate for four subjects was next tested against each other using paired t test. To assess the effect of chemo-fMRI manipulations, spiking activity was computed in experimental and control animals as described above and segmented into one-minute bins. We next computed the channel-averaged firing rate for each segment, and normalized this value with respect to the firing rate recorded during baseline (pre-CNO) period. The resulting baseline-normalized firing rate index was then used to assess changes in spiking rate upon CNO injection in the two experimental cohorts.To quantify effectiveness of Kir2p-values were corrected using a Benjamini–Hochberg FDR correction.To determine the time lag at which different firing rate samples from the same channels could be considered as approximately statistically independent, we computed for each subject the autocorrelation of the channel-averaged firing rate for each subject and computed the time lag after which the autocorrelation function drops below the 95th percentile. We then, for each subject, retained samples of the baseline-normalized firing rate at different times separated by the above obtained lags. We next separately analyzed the baseline-normalized rates in three different periods: 0–15 min (transient time), 15–35 min, and 35–55 min after CNO the injection (active time). We pooled all the retained data points in these windows both over time and over subjects and then compared the median between the two populations using a two-sided Wilcoxon rank-sum test. The obtained LFP spectrograms were computed using a Fourier transform with a Kaiser window with a frequency resolution of 0.15 Hz, temporal resolution of 6 s, and with 50% overlapping windows. Spectrograms and their differences were smoothed in time with the resolution of 30 s, and in frequency with the resolution of 1 Hz using a median filter. To quantify the effect of CNO on LFP rhythms, we computed a spectrogram modulation index as follows. First, we computed the channel-averaged spectrograms for the duration of the baseline recording. Next, we averaged time-frequency spectral profiles over time, resulting in frequency-resolved spectral profiles. The effect of CNO was next assessed by computing a modulation index, defined as the ratio of channel-averaged spectrogram after injection minus baseline, time-averaged spectrogram, and the sum of the same quantities, for every time window and for every frequency. This modulation index ranges between -1 and 1 and describes the changes due to drug injection over time for each frequency.To obtain a statistical assessment of CNO effects across groups and bands, we computed the autocorrelation of spectrograms for every subject at every frequency, using (as for our assessment of firing rate) only spectrograms computed at time points far enough to be approximately statistically independent. The time lag to determine such approximately independent points was identified as the interval after which the spectrum’s autocorrelation function dropped below the 95th percentile. We next computed the median of the modulation index over different frequency bands defined as follows: slow (0.1–1 Hz), δ (1–4 Hz), θ (4–8 Hz), α (8–12 Hz), β (12–30 Hz), and ƴ (30–70 Hz). Data within each band were pooled over uncorrelated time points (determined as above by taking time samples separated by lags at which autocorrelation became negligible) and over subjects, and the population medians were compared using two-sided Wilcoxon rank-sum tests, followed by FDR correction.83 with a 50% overlapping window of 2 s length. Coherence was calculated for every 60-s bin of channel-averaged recordings. Temporal smoothing was carried out using a 60-s median filter as described above. CNO spectrograms (30–40 post CNO injection window) were normalized with respect to the last 3 min of pre-CNO baseline using a modulation index as before. To obtain a quantifiable assessment of the CNO effect across different groups and bands, data within each band were pooled into 60-s bins. Subject and the population medians were compared for each region separately using one-sided Wilcoxon rank-sum tests, followed by FDR correction. The use of 60 s bins was motivated by estimations of the time lags at which autocorrelation of electrophysiological signals drops below the 95th percentile value (and thus samples are approximately independent) as described above.Channel-averaged spectrograms were preprocessed as described above. Raw spectral power coherence was assessed by computing the magnitude of squared coherency using Welch’s overlapped averaged periodogram method41, we computed LFP data spectrogram for the last 10 min of baseline and 30–40 min of post injection window, using a moving window of 2 s width and 0.75 percent overlap, resulting in an estimation of the resulting ultra-slow power for each 0.5 s interval. The ϒ-band envelope was computed as the integrated power of the spectrograms in the ϒ band 30–70 Hz46. The power spectrum of this time series was next computed, after correction for 1/f component46, revealing a peak in the 0.02–0.05 Hz region. Interareal coherence was then computed as described above for both experimental and control mice. To assess the effect of chemogenetic manipulations, we defined a coherence modulation index as described above for other frequency bands. Between group statistical assessments were carried out using two‐sided Wilcoxon rank‐sum tests, followed by FDR correction.To assess changes in ultra-slow fluctuations in the ϒ band envelope of LFP, following the work from Nir et al.To quantify interregional phase coupling, LFP data were first filtered using a third order Butterworth filter in delta band, and the instantaneous phase of each channel was computed by taking the phase of the analytical signal resulted from the Hilbert transform. For all possible pairs of channels belonging to two different regions, we next computed the corresponding Phase Locking Value (PLV) as follows:To understand whether the increase in δ and slow LFP power observed with DREADD-induced inhibition could be explained by selective elimination of spikes not occurring at the preferred, most excitable, phase of the considered oscillation, we simulated 10 s epochs of spikes locked to a cosine “LFP” wave oscillating at 1 Hz. In the first scenario, representing the DREADD conditions, we generated 100 spikes (rate of 10 spikes per second) tightly distributed around the preferred phase π with values taken from a von Mises distribution with an extremely high value (20) of the concentration parameter. For the second case (representing sham condition), we added 100 more spikes distributed almost randomly across phases, with values taken from a von Mises distribution with an extremely low value (0.5) of the concentration parameter. We then smoothed spike temporal components with a Gaussian kernel (100 ms width) and computed the power spectra of the resulting spike train with the multitaper method (Matlab pspectrum function).We computed at each time point the phase of the LFP in a given frequency band as the angle of the Hilbert transform of the band-passed LFP. We considered for this analysis the slow and δ bands. Signal in each band was band-passed using a 3rd order Butterworth filter. To measure the locking of spikes to specific phases of each band, we considered the distribution of the LFP phase values at the time of each MUA spike. From this distribution, we computed the phase locking value (PLV) as 1 minus the circular variance of this distribution (Methods Section “Multielectrode coherence”). PLV ranges from 0 (no locking or relationship between phase and spike times) to 1 (perfect locking of spikes to a certain phase). As for other quantities, we also computed a PLV modulation index as the difference of PLV values between the active-drug and baseline periods divided by the sum of PLV values in the active-drug and baseline periods. A two-sided Wilcoxon was used to check if the median PLV modulation index is higher for the experimental data with respect to control data.Violin plot representations of all electrophysiological analyses include individual statistically independent points (see above) used for intergroup comparisons. Plots were generated using Prism Graphpad 9.1. Plot truncation at extremities is introduced by the software to avoid representation of kernel density-related fictitious values above the highest data value or below the smallest.84.To characterize the phase differences across areas, we computed the distribution across time of the difference in the instantaneous phase (computed as explained above) of PFC and Rs electrode pairs. From this distribution, we considered a channel pair to have significant PLV (see “Multielectrode coherence” section above) if its PLV value exceeded the 95th percentile of surrogate PLV distribution obtained by shuffling LFPs in time prior to filtering, and if the same PLV value was also greater than 0.1. We report in Fig. Further information on research design is available in the Supplementary InformationReporting Summary


Monoclonal antibodies targeting a variety of epitopes have been isolated from individuals previously infected with SARS-CoV-2, but the relative contributions of these different antibody classes to the polyclonal response remains unclear. Here we use a yeast-display system to map all mutations to the viral spike receptor-binding domain (RBD) that escape binding by representatives of three potently neutralizing classes of anti-RBD antibodies with high-resolution structures. We compare the antibody-escape maps to similar maps for convalescent polyclonal plasmas, including plasmas from individuals from whom some of the antibodies were isolated. While the binding of polyclonal plasma antibodies are affected by mutations across multiple RBD epitopes, the plasma-escape maps most resemble those of a single class of antibodies that target an epitope on the RBD that includes site E484. Therefore, although the human immune system can produce antibodies that target diverse RBD epitopes, in practice the polyclonal response to infection is skewed towards a single class of antibodies targeting an epitope that is already undergoing rapid evolution. Emerging SARS-CoV-2 mutants may escape neutralization by antibodies. Here, the authors use deep mutational scanning to identify mutations in the RBD that escape human monoclonal antibodies or convalescent plasmas. These emerging lineages have mutations at <1% of all residues in the viral spike, and at no more than 3 of the ~200 residues in the spike receptor-binding domain (RBD)—yet these handfuls of mutations often substantially erode and in some cases even ablate the polyclonal neutralizing antibody response elicited by infection16.Control of the SARS-CoV-2 pandemic will depend on widespread population immunity acquired through infection or vaccination. But a little over a year into the pandemic, a proliferating number of new viral lineages are rising in frequency21, although antibodies that target the NTD also contribute to neutralization24. Structural and binding competition studies have shown that the most potently neutralizing anti-RBD antibodies target several distinct epitopes on the RBD’s receptor-binding motif27. However, the contributions of these different classes of RBD-targeting antibodies to the overall activity of the polyclonal antibody response remain less clear. It is therefore important to systematically determine both how viral mutations impact each antibody class, and how these antibody-specific effects shape the overall effects of viral mutations in a polyclonal context.A substantial fraction of the neutralizing activity of polyclonal antibody response to SARS-CoV-2 infection is due to antibodies that target the RBD29. We make these measurements by using a deep mutational scanning approach to systematically map how all RBD amino-acid mutations affect binding to yeast-displayed RBDs30 The resulting escape maps allow us to systematically compare how RBD mutations affect binding by the monoclonal antibodies, and we find that the antibodies cluster in the space of viral escape in a way that largely recapitulates prior classifications based on structural analyses of the antibody epitopes. However, some of the potently neutralizing monoclonal antibodies contribute very little to the escape maps of the polyclonal plasmas, even for individuals from whom the antibodies were isolated. Instead, the plasma-escape maps usually most resemble a single antibody class  that targets the face of the receptor-binding ridge that is accessible in both up and down RBD conformations. Unfortunately, a mutation that escapes this antibody class (E484K) is present in many emerging viral lineages, including B.1.351, P.1, P.2, and B.1.5266. We suggest that the skewing of the RBD-targeting polyclonal response toward a single antibody class is a factor in enabling a small number of viral mutations to sometimes substantially erode neutralizing antibody immunity.Here, we comprehensively map RBD mutations that reduce binding by structurally characterized representatives of three classes of neutralizing monoclonal antibodies that target the RBD’s receptor-binding motif, as well as polyclonal plasmas from convalescent individuals from whom some of the antibodies were isolated31. Antibodies targeting the RBD have been divided into four major classes based on structural analyses of their epitopes; two with epitopes overlapping with the ACE2-binding site (class 1 and class 2), potent neutralizers that do not directly bind to the ACE2 contact surface (class 3), and antibodies that target a cryptic epitope outside of the receptor-binding motif and are generally less potent (class 4)25. We focused our studies on several antibodies representative of the first three classes of potently neutralizing receptor-binding motif-targeting antibodies. Class 1 antibodies bind the face of the receptor-binding motif that is accessible only when the RBD is in the up conformation  to enrich for cells expressing RBD mutants that escaped antibody binding . We did this for the seven antibodies shown in Fig. 36, including class 4 antibodies, which bind to the RBD outside the receptor-binding motif and are generally less potently neutralizing31. Antibodies with similar escape mutations are located close to one another in the multidimensional scaling projection, and antibodies with very distinct escape mutations are far apart . All sites at which mutations strongly escape binding are in direct (<4 Å) or proximal (4–8 Å) contact with antibody in the resolved structures . Only 2304 of the 3819 possible amino-acid mutations to the RBD meet these criteria, and some sites have no tolerated mutations. For instance, G416 and R457 are both in the structural epitope of C105, but these sites have no tolerated mutations and thus do not appear in the escape map . The plasmas from both cohorts cluster together in the space of binding escape, but far from some of the antibodies .To more broadly compare how antibodies of different classes contribute to the convalescent plasma-escape maps, we used multidimensional scaling to project 22 antibodies and 28 polyclonal plasmas into a two-dimensional space of binding-escape mutations  had visible effects on the polyclonal plasmas, but again less so than for class 2 antibody sites , then class 1 or 3 antibodies might dominate for the remaining anti-RBD-antibody activity.To visualize the escape maps in terms of the RBD’s three-dimensional structure, we projected onto the surface of the RBD the total escape at each site averaged across all antibodies in a class or all convalescent plasmas in a cohort Fig. . Again, tes Fig. . Howeverons Fig. . Overall7. We hypothesized that the mutations selected during viral passage would reduce antibody binding without impairing ACE2-binding affinity. Accordingly, we examined how all of the selected mutations affected both antibody binding (as measured in the current study) and ACE2 affinity . Figure We assessed how well our escape maps predicted the actual antibody-escape mutations that arose when the virus was grown in the presence of the antibodies. Prior work selected viral escape mutants by passaging chimeric vesicular stomatitis virus (VSV) encoding the SARS-CoV-2 spike in the presence of several of the monoclonal antibodies we mapped in this study7. There was generally good agreement between our escape maps and these previously measured effects of mutations on viral neutralization. Nearly all mutations with a > 100-fold reduction in neutralization also had large effects in our escape maps, although in a few cases mutations with more moderate effects on neutralization were not prominent in the escape maps  largely shapes how RBD mutations affect binding by polyclonal plasmas, even for individuals from whom potent neutralizing antibodies of other classes were isolated. A similarly unequal immunodominance of different epitopes has also been described for other viral antigens, such as influenza hemagglutininVH1-2, VH3-53, VH1-69)51. Consistent with our work here showing that class 2 antibodies shape how mutations affect polyclonal plasma binding, mutations at the site that most strongly affects binding by this antibody class (E484) have arisen multiple times in emerging viral lineages6. Therefore, our results show the importance of thinking about antigenic evolution in the context of different classes of antibodies that recognize different epitopes on the RBD.The importance of class 2 antibodies in the RBD-targeting portion of polyclonal plasma could be due in part to the twin facts that their epitope is exposed in both up- and downconformations of the RBD, and that such antibodies are often generated from frequently observed germline genes  have been reported55. Fortunately, no major viral lineages currently contain mutations to all three epitopes. However, we suggest the appearance of such a variant would be a worrying development and should be monitored closely.Framing viral antigenic evolution in terms of different classes of antibody epitopes is useful for interpreting the impacts of viral mutations and forecasting where in the RBD new escape mutations may arise in the future. Consistent with our work showing that mutations at class 2 antibody epitopes generally cause the largest reductions in the binding of polyclonal anti-RBD plasma antibodies elicited by infection, many emerging SARS-CoV-2 lineages have already acquired a mutation (E484K) at the site that most potently escapes antibodies of this class. Once viruses have escaped class 2 antibodies, antibodies of other classes  will contribute to most remaining RBD-targeted antibody immunity. In this respect, it is noteworthy that some of the most prominent emerging viral lineages with E484K have also acquired a mutation  at the site that most potently escapes binding by class 1 antibodies. Moreover, the B.1.427/429 and B.1.617.2 viral lineages contain a moderate class 3 escape mutation (L452R)21. Plasma samples profiled in this study were obtained 21–35 days post-symptom onset21. Samples were obtained upon written consent from community participants under protocols approved by the Institutional Review Board of the Rockefeller University (DRO-1006). All samples were heat-inactivated prior to use by treatment at 56 °C for 60 min. Prior to use in each assay, plasma samples were centrifuged for 15 min at 2000 × g to pellet platelets.Plasma samples were previously described and collected as part of a prospective longitudinal cohort study of SARS-CoV-2 convalescent individuals in New York, NY21. Briefly, the IGH, IGL, and IGK genes were sequenced using IgG-specific primers from single-cell sorted RBD+, CD20+ memory B cells (CD3−CD8−CD14−CD16−CD20+Ova−RBD-PE+RBD-AF647+). Recombinant monoclonal antibodies were produced and purified, as previously described57. Antibodies were produced with a human IgG1 heavy chain and human IgK  or human IgL2  constant regions. These antibodies were previously structurally characterized in complex with SARS-CoV-2 S trimer29. A subset was functionally characterized in refs. 58. The PBD accessions for the antibody-S complex structures are 6XCM and 6XCN for C105, 7C01 for LY-CoV016, 7K8S and 7K8T for C002, 7K8X and 7K8Y for C121, 7K90 for C144, 7K8Z for C135, and 7K8V for C11029. The protein sequences for these antibodies are available at the aforementioned PDB accession numbers.Antibodies were isolated from individuals in the cohort above as previously described30 with previously described duplicate yeast-displayed mutant RBD libraries32. These libraries were generated in the RBD background of the SARS-CoV-2 isolate Wuhan-Hu-1  via NNS codon tiling PCR mutagenesis, which introduced an average of 2.7 amino-acid mutations per library variant. RBD variants were linked to unique 16-nucleotide barcode sequences to facilitate downstream sequencing and bottlenecked to library sizes of ~100,000 uniquely barcoded variants. The libraries contain 3804 of the 3819 possible amino-acid mutations, with >95% present as single mutants on at least one barcode in the libraries. We previously used these libraries to measure the effect of all RBD mutations on yeast-surface RBD expression and ACE2 affinity32. These libraries were sorted to eliminate variants that lose ACE2 binding prior to mapping the antibody-escape variants30.Monoclonal antibody and polyclonal clonal plasma selection experiments were performed in biological duplicate using a deep mutational scanning approach30. Specifically, 9 OD aliquots of RBD libraries were thawed and grown overnight at 30 °C 275 rpm in 45 mL of SD-CAA . Libraries were diluted to an OD of 0.67 in SG-CAA + 0.1% dextrose , and incubated for 16–18 h at room temperature with mild agitation to induce RBD surface expression. For each antibody selection, 20 OD units of induced cells were washed twice with PBS–BSA (0.2 mg/mL), and incubated in 4 mL of PBS–BSA with monoclonal antibody or plasma for 1 h at room temperature with gentle agitation. Incubations were performed with 400 ng/mL for each monoclonal antibody  or with a sub-saturating dilution of polyclonal plasma such that the amount of fluorescent signal due to plasma antibody binding to RBD was approximately equal across plasmas . Labeled cells were washed with ice-cold PBS–BSA followed by secondary labeling for 1 h at 4 °C in 2.5 mL of 1:200 PE-conjugated goat anti-human-IgG (Jackson ImmunoResearch 109-115-098) to label for bound monoclonal antibody or 1:200 Alexa-647-conjugated goat anti-human-IgA+IgG+IgM (Jackson ImmunoResearch 109-605-064) to label for bound plasma antibodies and 1:100 FITC-conjugated anti-Myc  to label for RBD surface expression. Labeled cells were washed twice with PBS–BSA and resuspended in 2.5 mL of PBS. Yeast expressing the unmutated SARS-CoV-2 RBD were prepared in parallel to library samples, labeled at the same 400 ng/mL and 100× reduced 4 ng/mL antibody concentrations for the monoclonal antibodies, and with 1× and 10× reduced plasma concentrations for the polyclonal plasmas.Antibody labeling and selection were performed essentially as described by Greaney et al.Yeast cells expressing RBD variants with substantially reduced antibody binding were selected via fluorescence-activated cell sorting (FACS) on a BD FACSAria II, using FACSDiva software, version 6.1. For monoclonal antibody selections, FACS selection gates were drawn to capture 95% of yeast expressing unmutated SARS-CoV-2 RBD labeled at 100-fold reduced antibody concentration relative to library samples. For polyclonal plasma selections, FACS selection gates were drawn to capture 2.8–5% of the RBD mutants with the lowest amount of plasma binding for their degree of RBD expression Fig. . Nearly 32. Specifically, a primer with the sequence 5′-AATGATACGGCGACCACCGAGA-3′ was used to anneal to the Illumina P5 adaptor sequence, and the PerkinElmer NextFlex DNA Barcode adaptor primers with the sequence 5′-CAAGCAGAAGACGGCATACGAGATxxxxxxxxGTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT-3′ (where xxxxxxxx indicates the sample index sequence) were used to anneal to the Illumina P7 adaptor sequence and append sample indexes for sample multiplexing. Barcodes were sequenced via 50 bp single-end reads on an Illumina HiSeq 2500, targeting at least 2.5× as many sequencing reads as FACS-selected cells, and pre-sort reference populations of at least 2.5e7 reads.Plasmid samples were prepared from up to 7.5 OD units (4e7 CFUs) of overnight cultures of antibody-escaped cells, and 30 OD units (1.6e8 CFUs) of pre-selection yeast populations (Zymoprep Yeast Plasmid Miniprep II) per the manufacturer instructions, with the addition of a −80 °C freeze–thaw step prior to cell lysis. The 16-nucleotide barcode sequences identifying each RBD variant were amplified by PCR and prepared for Illumina sequencing exactly as described previously30, with minor modifications as noted below. Specifically, we used the dms_variants package  to process Illumina sequences into counts of each barcoded RBD variant in each pre-sort and antibody-escape population using the barcode/RBD look-up table from Starr et al.32. Markdown renderings of these steps in the computational analysis are at https://github.com/jbloomlab/SARS-CoV-2-RBD_MAP_Rockefeller/blob/main/results/summary/aggregate_variant_counts.md and https://github.com/jbloomlab/SARS-CoV-2-RBD_MAP_Rockefeller/blob/main/results/summary/counts_to_cells_ratio.md.Escape fractions were computed as described in Greaney et al.30. These escape fractions represent the estimated fraction of cells expressing that specific variant that falls in the antibody escape bin, so a value of 0 means the variant is always bound by antibody and a value of 1 means that it always escapes antibody binding. We then applied a computational filter to remove variants with low sequencing counts or highly deleterious mutations that might cause antibody escape simply by leading to poor expression of properly folded RBD on the yeast cell surface. Specifically, we ignored all variants with pre-selection sequencing counts that were lower than the counts for the 99th percentile of the stop-codon-containing variants because stop-codon variants are largely purged by the earlier sorts for RBD expressing and ACE2-binding variants and so any residual presence provides an indication of low-count noise. Next, we removed any variants that had poor RBD expression or ACE2 binding, or contained mutations that individually cause poor RBD expression and ACE2 binding to eliminate misfolded or non-expressing RBDs. Specifically, we removed variants that had (or contained mutations with) ACE2-binding scores < −2.35 or expression scores < −1, using the variant- and mutation-level deep mutational scanning scores32. Note that these filtering criteria are slightly more stringent than those used in Greaney et al. (2021)30 but are identical to those used in Greaney et al. and Starr et al33. The ACE2-binding cutoff of −2.35 is used to represent the binding of RaTG13 to human ACE232, which possesses the lowest known affinity capable of mediating cell entry59. The RBD expression cutoff of −1 is used to eliminate mutations that have as large an expression deficit as mutations to core disulfide residues. 2034 of the 3819 possible RBD amino-acid mutations passed these filtering steps and were included in our escape maps. All previously reported escape-mapping data36 were reanalyzed in this study with the parameters listed above. A markdown rendering of the computation of the variant-level escape fractions and the variant filtering is at https://github.com/jbloomlab/SARS-CoV-2-RBD_MAP_Rockefeller/blob/main/results/summary/counts_to_scores.md.For each antibody selection, we then computed the escape fraction for each barcoded variant using the deep sequencing counts for each variant in the original and antibody-escape populations and the total fraction of the library that escaped antibody binding via the formula provided in Greaney et al.60 implemented in the dms_variants package, as detailed at . In this fitting, we excluded variants that contained mutations that were not seen as either single mutants or in at least two multiple-mutant variants. We then computed the estimated effect of each mutation as the impact of that mutation on the observed phenotype scale transformation of its latent phenotype as computed using the global-epistasis models, and applied a floor of zero and a ceiling of 1 to these escape fractions. All of the above analysis steps were performed separately for each of the duplicate mutant libraries. We then only retained mutations that passed all of the above filtering and were measured in both libraries or had at least two single-mutant variant measurements in one library. The reported scores throughout the paper are the average across the libraries; these scores are also in Supplementary Data https://github.com/jbloomlab/SARS-CoV-2-RBD_MAP_Rockefeller/blob/main/results/summary/scores_to_frac_escape.md.Because some library variants contain multiple amino-acid mutations, we next deconvolved variant-level escape scores into escape fraction estimates for single mutations using global-epistasis modelshttps://github.com/jbloomlab/SARS-CoV-2-RBD_MAP_Rockefeller/blob/main/results/summary/call_strong_escape_sites.md.For plotting and analyses that required identifying RBD sites of strong escape  of the same monoclonal antibodies and polyclonal plasmas against some RBD point-mutants7. The numerical IC50 values were extracted from figures in Weisblum et al.7 using the WebPlotDigitizer tool v4.4 (https://apps.automeris.io/wpd/). We convert those previously measured IC50s to fold-change IC50 relative to wildtype RBD. The numerical IC50s found in Weisblum et al.7 are also tabulated at https://github.com/jbloomlab/SARS-CoV-2-RBD_MAP_Rockefeller/blob/main/experimental_data/data/weisblum_ic50.csv.In Fig. 38 as of May 11, 2021 were downloaded and aligned via mafft61, version 7.471. Sequences from non-human origins and sequences containing gap or ambiguous characters were removed, as were sequenced with extremely high numbers of RBD mutations relative to other sequences, leaving 679,502 retained sequences. All RBD amino-acid mutations were enumerated compared to the reference Wuhan-Hu-1 SARS-CoV-2 RBD sequence . We acknowledge all contributors to the GISAID EpiCoV database for their sharing of sequence data .For the analysis in Fig. https://jbloomlab.github.io/dmslogo/) version 0.6.2; a markdown rendering of the code that creates these logo plots is at https://github.com/jbloomlab/SARS-CoV-2-RBD_MAP_Rockefeller/blob/main/results/summary/escape_profiles.md. For each plasma, the y axis is scaled to be the greatest of (a) the maximum site-wise escape metric observed for that plasma, (b) 20× the median site-wise escape fraction observed across all sites for that plasma, or (c) an absolute value of 1.0 .The static logo plots in the paper were created using dmslogo 62.The interactive visualizations of the escape maps and their projections on the RBD-antibody structures available at 29. Structural distances were computed using the bio3d package version 2.4.0 in R version 3.6.263 Surface representations of the RBD for non-antibody-bound structures utilize PDB 6M0J64.The static structural views Figs.  and S5 i25 and colored accordingly. We define the class 1 epitope as residues 403 + 405 + 406 + 417 + 420 + 421 + 453 + 455-460 + 473-476 + 486 + 487 + 489 + 504, the class 2 epitope to be residues 455 + 456 + 472 + 483-487 + 489 + 490 + 491 + 492 + 493 + 494, and the class 3 epitope to be residues 345 + 346 + 437-452 + 496 + 498-501. There are five residues that overlap between the class 1 and class 2 epitopes: 455 + 456 + 486 + 487 + 489.In many of the visualizations, the RBD sites are categorized by epitope region , defined by Barnes et al.Further information on research design is available in the Supplementary InformationPeer Review FileDescription of Additional Supplementary FilesSupplementary Data 1Reporting Summary