BUSCADOR RECOLECTA

Additional file 3: Supplementary Fig. 3. A) Dose–response analyses of the effect of anti-CD98hc-DM1 on the proliferation of parental and CD98hc CRISPR #5 and #11 HT29 cells. Cells were treated with anti-CD98hc-DM1 at the indicated doses for four days. Results are shown as the mean ± SD of quadruplicates of an experiment repeated three times. B) Expression of CD98hc in normal human fibroblasts (NHF) and immortalized keratinocytes (HaCaT), compared to CRC cell lines. Cell extracts (20 µg) were used to identify CD98hc by Western blot with the anti-CD98hcV509 antibody. Calnexin was used as a loading control. C) Dose–response analyses of the anti-CD98hc-DM1 ADC on NHF and HaCaT, compared to HT29 cells. Cells were treated with the ADC for four days at the indicated doses. The data are plotted as the percentage of MTT metabolization with respect to control. Results are shown as the mean ± SD of quadruplicates of an experiment repeated two times. D) Evaluation of the effect of anti-CD98hc-DM1 (10 nM, 48 h) on the distribution of the different cell cycle phases in HT29 and HCT116 cell lines. E) Immunofluorecescence analyses of the action of anti-CD98hc-DM1 on spindle assembly and organization on HCT116 cells treated with CD98hc-DM1 (10 nM) for 48 h. β-Tubulin (green), DAPI (blue). Scale bars = 7.5 µm. F). Detection of giant multinucleated cells or altered nuclear structures after anti-CD98hc-DM1 treatment. HCT116 and HT29 cells were treated with 10 nM anti-CD98hcECTO-DM1 for 72 h, fixed and stained for nucleoporin p62 (red) and DNA (blue). Scale bar = 10 μm. The arrows indicate giant multinucleated cells., Instituto de Salud Carlos III Consejo Superior de Investigaciones Científicas Junta de Castilla y León ALMOM ACMUMA UCCTA CRIS Cancer Foundation Agencia Estatal de Investigación Consejo Superior de Investigaciones Cientificas (CSIC), Peer reviewed

Additional file 4: Supplementary Fig. 4. A) Kaplan–Meier survival curve of mice from the experiment performed in Fig. 6A. The Kaplan–Meier survival plot was created using a tumor volume threshold of 1,000 mm3. P values were calculated using one-sided log-rank tests. B) Effect of the anti-CD98hc ADC on the weight of mice xenografted with HT29 cells. Data are plotted as mean ± SD of six mice/group. C) Analysis of the antitumoral effect of naked anti-CD98hc and DM1 on tumor growth in nude mice implanted with HT29 cells. Arrows indicate days of administration of anti-CD98hc (15 mg/Kg) or DM1 (0.14 mg/Kg). Data are plotted as mean tumor volumes ± SEM. P values were calculated using Student’s t test (two-sided). D) Kaplan–Meier survival curve of mice from the experiment of panel C. The Kaplan–Meier survival plot was created using a tumor volume threshold of 650 mm3. P values were calculated using one-sided log-rank tests. E) Expression levels or phosphorylation of proteins involved in cell cycle and apoptosis in the tumors of the experiment performed in Fig. 6A. Tumor samples were obtained on day 21 after initiation of treatments (seven days after the last treatment). Tissue extracts of the tumors were used to analyze the levels of expression of pH3, PARP, pH2AX, pCDK1 and cleaved Caspase 3. Stain free blot was analyzed to verify equal loading. F) Quantitation of the levels of DM1 (data shown in Fig. 6B), pH3, PARP, pH2AX, pCDK1 and cleaved Caspase 3 of the experiments shown in panel E. The graphs represent the mean intensity (arbitrary units) ± SD of the different proteins present in control (C) or treated (anti-CD98hc-DM1) mice groups. P values were calculated using Student’s t test (two-sided). G) Immunohistochemical detection of CD98hc in PDX BT6224 (P2M1: passage 2, mouse #1) using the anti-CD98hcV509 antibody. H) Kaplan–Meier survival curve of mice from the experiment performed in Fig. 6E. The Kaplan–Meier survival plot was created using a tumor volume threshold of 800 mm3. P values were calculated using one-sided log-rank tests. I) Effect of the anti-CD98hc ADC on the weight of mice xenografted with PDX BT6224. Data are plotted as mean ± SD of four mice/group. J) Quantitation of the levels of DM1 of the experiments performed in Fig. 6F. The graphs represent the mean intensity (arbitrary units) ± SD of IgG Heavy and Light chains coupled to DM1 present in control (C) or treated (anti-CD98hc-DM1) groups. P values were calculated using Student’s t test (two-sided)., Instituto de Salud Carlos III. Consejo Superior de Investigaciones Científicas (España). Junta de Castilla y León. Fundación CRIS contra el Cáncer., Peer reviewed

To describe the incorporation of monoclonal antibodies (mAb) in real-world (RW) practice for the treatment of patients with relapsed refractory multiple myeloma (RRMM) in a setting with other treatment alternatives. This was an observational, multicenter, ambispective study of RRMM treated with or without a mAb. A total of 171 patients were included. For the group treated without mAb, the median (95% CI) progression-free survival (PFS) to relapse was 22.4 (17.8-27.0) months; partial response or better (≥PR) and complete response or better (≥CR) was observed in 74.1% and 24.1% of patients, respectively; and median time to first response in first relapse was 2.0 months and in second relapse was 2.5 months. For the group of patients treated with mAb in first or second relapse, the median PFS was 20.9 (95% CI, could not be evaluated) months; the ≥ PR and ≥ CR rates were 76,2% and 28.6%, respectively; and the median time to first response in first relapse was 1.2 month and in second relapse was 1.0 months. The safety profiles for the combinations were consistent with those expected. The incorporation of mAb in RW practice for the treatment of RRMM has shown good quality and speed of response with a similar safety profile shown in randomized clinical trials., This study was sponsored by Janssen-Cilag. Janssen-Cilag participated in the study design, data analysis and drafting of the manuscript, Peer reviewed

4 files, Supplementary material for the article http://dx.doi.org/10.3390/biology9100337, Doc file: Figure S1: Number of turbot cells and ciliates in the peritoneal cavity; Figure S2: Micrographs of ciliates at different stages of infection; Figure S3: qPCR validation of RNA-seq findings; Table S1: Sample information; Table S2: Primer sequences used in the qPCR analysis.-- File S1: Excel file showing the contigs that were DE in P. dicentrarchi at 1, 2, 4 hpi, the fold change, p-value, and the gene names.-- File S2: Excel file showing the contigs that were DE in turbot peritoneal cells at 1, 2, 4 hpi, the fold change, p-value, and the gene names.-- File S3: Excel file showing the contigs that were DE in turbot peritoneal cells at 12 and 48 hpi, the fold change, p-value, and the gene names, Peer reviewed

Additional file 1: Text S1. Translated questionnaire to include donor in Cohort II. Fig. S1. Impact of genetic background on numbers of circulating immune cells. Each color and symbol indicate members of one family. Fully open symbols represent a centenarian. Semi-open symbol (orange) represents a sibling of a centenarian. Dashed lines indicate the available age-matched reference values produced with flow cytometry panels highly similar to the panels used in this study (earlier or later prototypes of these panels). For B- and T-cell subsets, reference lines indicate a cohort aged 60–79 years. For innate myeloid populations, reference lines indicate a cohort > 55 years old. In plots without dashed lines, no published reference values from highly similar flow cytometry panels were available. Fig. S2. Results of the pilot study to evaluate the calcium flux upon stimulation of the B-cell receptor (BCR) with IgG and IgM Fab fragments. (A) Measurement of calcium release (‘flux’) after B-cell stimulation with IgM Fabs in pre-GC B cells (CD27-IgA-IgG-) or unswitched memory B cells (CD27+IgA-IgG-). (B) Measurement of calcium release (‘flux’) after B-cell stimulation with IgG Fabs in CD27-IgG+ memory B cells (CD27-IgD-IgA-) or CD27+IgG+ memory B cells (CD27+IgD-IgA-). Ionomycin was added to calculate maximum calcium release. N = 14. Pre-GC; pre-Germinal Center, MBC; memory B cell. Fig. S3. Assessment of B-cell activation in all p.P522R-carriers and non-carriers upon BCR stimulation. Measurement of calcium release (‘flux’) after B-cell stimulation with IgM Fabs in pre-GC B cells (CD27-IgG-IgA-) (A) or unswitched memory B cells (CD27+IgG-IgA-) (B) in cohort I. Ionomycin was added to calculate maximum calcium release. Differences between carriers and non-carriers were evaluated by comparing the area under the curve (AUC) of the total Fab stimulation (from stimulation until the moment ionomycin was added, ~ 10 min, flux intensity and duration), the peak of the response after Fab stimulation (the 5 highest points after the Fabs were added to the cells; flux intensity), and after ionomycin was added (to determine the maximum flux). AUC was calculated only for points that were higher than baseline value (unstimulated sample). N = 31 (two samples were lost due to technical failure). No significant differences were observed. Pre-GC; pre-Germinal Center. Fig. S4. Phagocytosis and ROS production in innate immune cell subsets after stimulation with pHRodo™ Green E. coli Bioparticles (FcR/PLCγ2-dependent stimulation). To evaluate the outcome of the phagocytosis assays, three different readouts were used per population: % of cells that were phagocytosing, the average amount of particles phagocytosed per cell, and the ROS production upon phagocytosis. These three readouts were further combined into one value: the normalized ROS. These values are presented for the CD62L+ classical monocyte (cMo) subset (A), intermediate monocytes (iMo) (B), neutrophils (C) CD14- and CD14dim myeloid dendritic cells (mDCs) (D,E), and non-phagocytosing plasmacytoid dendritic cells (pDCs) (F). Lastly, the outcomes for T cells (negative control) are shown (G). Mann-Whitney U test was used to evaluate differences between carriers and non-carriers, but no statistically significant differences were found. N = 14. In two donors, monocytes could not be divided into subsets due to absence of a differentiating antibody in the prepared antibody cocktail, therefore, in panel A and B, only 5 non-carriers and 7 carriers are shown. Dashed lines indicate the background level of ROS (ROS production in negative control population; T cells). All outcomes were corrected for background or baseline activation by subtracting the value of the control (incubated on ice) from the activated (incubated at 37 °C) sample. Negative values (caused by higher background in control samples than activated samples in cell populations that did not perform phagocytosis) were set to 0. Fig. S5. ROS generation in innate immune cell subsets in p.P522R-carriers and non-carriers upon stimulation with PMA (FcR/PLCγ2-independent stimulation). N = 14. In two donors, monocytes could not be divided into subsets due to absence of an antibody in the prepared antibody cocktail, therefore, in panel A-D, only 5 non-carriers and 7 carriers are shown. Dashed lines indicate the background level of ROS (ROS production in negative control population; T cells). All outcomes were corrected for background or baseline activation by subtracting the value of the control (incubated on ice) from the activated (incubated at 37 °C) sample. Table S1. Description of all included families and additional donors. Table S2. Overview of the flow cytometry panels that were used in this study. Table S3. Phenotypic descriptions used to define B-cell subsets stained with EuroFlow PERISCOPE B-cell and plasma cell panel (BIGH) panel by manual analysis. Table S4. Phenotypic descriptions used to define T-cell subsets stained with EuroFlow PERISCOPE CD4 T-cell (TCD4) panel by manual analysis. Table S5. Phenotypic descriptions used to define T-cell and NK-cell subsets stained with the EuroFlow PERISCOPE CD8 cytotoxic T-cell (CYTOX) panel by manual analysis. Table S6. Phenotypic descriptions used to define innate immune cell (sub) sets stained with the EuroFlow PERISCOPE DC-Monocyte panel by manual analysis. Table S7. Polygenic Risk Score and SNP annotation for immune-related SNPs. Table S8. Control and assay tubes measured in the phagocytosis experiment. Table S9. Control and assay tubes measured when detection production of reactive oxygen species (ROS)., ZonMw Health Holland HorstingStuit Foundation, the Hans und Ilse Breuer Foundation and Stichting VUmc Fund H2020 Marie Skłodowska-Curie Actions, Peer reviewed

1 file, Supplementary material for the article https://doi.org/10.3390/biom10081184, Figure S1: Fermentations of L. brevis.-- Figure S2: Kinetic growth of P. fluorescens.-- Figure S3: Kinetic growth of B. subtilis.-- Figure S4: Economical evaluation of L. plantarum bioproduction costs.-- Figure S5: Economical evaluation of P. fluorescens, B. subtilis and S. epidermidis growth costs.-- Table S1: Composition of culture media.-- Table S2: Kinetic Parameters of L. plantarum cultures on FP media.-- Table S3: Kinetic Parameters of L. plantarum cultures on TP media.-- Table S4: Kinetic parameters of L. brevis cultures on FP media.-- Table S5: Kinetic parameters of L. brevis cultures on TP media.-- Table S6: Productive yields of LAB bioproductions.-- Table S7: Kinetic parameters of P. fluorescens cultures on FP media.-- Table S8: Kinetic parameters of P. fluorescens cultures on TP media.-- Table S9: Kinetic parameters of Phaeobacter sp. cultures on FP media.-- Table S10: Kinetic parameters of Phaeobacter sp. cultures on TP media.-- Table S11: Kinetic parameters of B. subtilis cultures on FP media.-- Table S12: Kinetic parameters of B. subtilis cultures on TP media.-- Table S13: Kinetic parameters of S. epidermidis cultures on FP media.-- Table S14: Kinetic parameters of S. epidermidis cultures on TP media, Peer reviewed

Additional file 1: Fig. S1. CrkL binds through the SH3N domain and with similar affinity to the four isolated PRMs of C3G. Fig. S2. Analysis of CrkL by sedimentation velocity. Fig. S3. ITC analysis of the binding of CrkL to single-PRM mutants of C3G. Fig. S4. Linear concentration dependence of the nucleotide exchange activity of phospho-C3G. Fig. S5. Binding of CrkL fragments and CrkII to C3G. Table S1. Constructs of human C3G in the vector pETEV15b-His-Halo-TEV for expression in E coli. Table S2. Oligonucleotides used to create constructs of C3G and for site directed mutagenesis. Table S3. Constructs of human C3G in the vectors for expression in mammalian cells. Table S4. Constructs of human CrkL and CrkII in the vectors for expression in E coli. Table S5. Oligonucleotides used to create constructs of CrkL and CrkII. Table S6. Oligonucleotides to subclone the abGFP4 nanobody in a modified pET22b vector. Table S7. Parameters of the CrkL/C3G interaction determined by ITC. Table S8. Hydrodynamic parameters of C3G and CrkL. Table S9. Parameters of the CrkL/C3G interaction determined by ITC and sedimentation velocity. Table S10. Parameters of the CrkL binding to single-PRM mutants of C3G determined by ITC. Table S11. Parameters of the binding of CrkL fragments to C3G determined by ITC., Universidad de Salamanca Ministerio de Ciencia e Innovación Consejería de Educación, Junta de Castilla y León Agencia Estatal de Investigación National Institute of Biomedical Imaging and Bioengineering Junta de Castilla y León Consejo Superior de Investigaciones Cientificas (CSIC), Peer reviewed

(A) Schematic illustration of the “auxin inducible degron” system. (i) The Cbk1 auxin degron strain (cbk1-aid, where aid denotes the auxin inducible degron) contains a version of Cbk1 in which the auxin inducible degron was fused to the C-terminus of CBK1 in its own locus. Protein expression is under CBK1 promoter and Cbk1-aid is able to perform wt Cbk1’s functions. The fusion was carried out in a yeast strain in which the F-box protein Tir1 is expressed constitutively under the control of ADH1 promoter. Tir1 binds to SCF and forms the E3 ubiquitin ligase SCF-TIR1 that recruits the E2 ubiquitin conjugating enzyme [38]. (ii) Following the addition of auxins, the F-box Tir1 is able to specifically recognise the aid tag fused to Cbk1. Then, E2 ubiquitin conjugating enzyme polyubiquitylates aid, which rapidly promotes the degradation of Cbk1-aid by the proteasome (iii). This system allows to study the immediate biological consequences after Cbk1 depletion. (B) ADH-TIR1 (YJW15) and cbk1-aid ADH-TIR1 (YMF3657) cells were grown in YPD before the addition of NAA and IAA auxins. Samples were taken at the indicated times to determine cell-cycle progression by flow cytometry. (C) Schematic representation of experimental set-up in which cells were grown in YPD and arrested in late anaphase by shifting the temperature to 37 °C before the addition of NAA and IAA auxins for 50 min. Next, cells were incubated with DMSO (i) or rapamycin (ii) for 20 min while still arrested in anaphase. Cells were released in the absence (i) or presence (ii) of rapamycin, and with the NAA and IAA auxins present in medium throughout the rest of the experiment. (D) cbk1-aid cdc15-2 (YMF3866) cells were grown as represented in C. Samples were taken at shown times to determine cell-cycle progression by flow cytometry ((i) and (ii)) and cell morphology by light microscopy in the absence (iii) or in the presence (iv) of rapamycin at 120 min after the release from late anaphase arrest. Scale bars indicate 5 μm. (E) (i) To study functionally compromised versions of Cbk1, we initially expressed both Cbk1 fused to aid and the altered Cbk1 protein whose sequence had been integrated as an extra copy together with 5′ and 3′ UTRs. Cells are not defective under permissive conditions as viability is supported by Cbk1-aid, whereas after the addition of auxins ((ii) restrictive conditions) Cbk1-aid is depleted and functional consequences of compromised Cbk1 expression could be determined. (F) cbk1-D475A cbk1-aid cdc15-2 (YMF4047) cells were cultured an analysed as in D. (G) As control, CBK1 cbk1-aid cdc15-2 (YMF4082) cells were grown and analysed as in D. FACS graphs can be found in the supplementary FACS file (S1 File)., pbio.3002263.s002.pdf, Peer reviewed

[Introduction]: Monitoring of innate myeloid cells (IMC) is broadly applied in basic and translational research, as well as in diagnostic patient care. Due to their immunophenotypic heterogeneity and biological plasticity, analysis of IMC populations typically requires large panels of markers. Currently, two cytometry-based techniques allow for the simultaneous detection of ≥40 markers: spectral flow cytometry (SFC) and mass cytometry (MC). However, little is known about the comparability of SFC and MC in studying IMC populations., [Methods]: We evaluated the performance of two SFC and MC panels, which contained 21 common markers, for the identification and subsetting of blood IMC populations. Based on unsupervised clustering analysis, we systematically identified 24 leukocyte populations, including 21 IMC subsets, regardless of the cytometry technique., [Results]: Overall, comparable results were observed between the two technologies regarding the relative distribution of these cell populations and the staining resolution of individual markers (Pearson’s ρ=0.99 and 0.55, respectively). However, minor differences were observed between the two techniques regarding intra-measurement variability (median coefficient of variation of 42.5% vs. 68.0% in SFC and MC, respectively; p<0.0001) and reproducibility, which were most likely due to the significantly longer acquisition times (median 16 min vs. 159 min) and lower recovery rates (median 53.1% vs. 26.8%) associated with SFC vs. MC., [Discussion]: Altogether, our results show a good correlation between SFC and MC for the identification, enumeration and characterization of IMC in blood, based on large panels (>20) of antibody reagents., Peer reviewed

[Introduction]: Monitoring of innate myeloid cells (IMC) is broadly applied in basic and translational research, as well as in diagnostic patient care. Due to their immunophenotypic heterogeneity and biological plasticity, analysis of IMC populations typically requires large panels of markers. Currently, two cytometry-based techniques allow for the simultaneous detection of ≥40 markers: spectral flow cytometry (SFC) and mass cytometry (MC). However, little is known about the comparability of SFC and MC in studying IMC populations., [Methods]: We evaluated the performance of two SFC and MC panels, which contained 21 common markers, for the identification and subsetting of blood IMC populations. Based on unsupervised clustering analysis, we systematically identified 24 leukocyte populations, including 21 IMC subsets, regardless of the cytometry technique., [Results]: Overall, comparable results were observed between the two technologies regarding the relative distribution of these cell populations and the staining resolution of individual markers (Pearson’s ρ=0.99 and 0.55, respectively). However, minor differences were observed between the two techniques regarding intra-measurement variability (median coefficient of variation of 42.5% vs. 68.0% in SFC and MC, respectively; p<0.0001) and reproducibility, which were most likely due to the significantly longer acquisition times (median 16 min vs. 159 min) and lower recovery rates (median 53.1% vs. 26.8%) associated with SFC vs. MC., [Discussion]: Altogether, our results show a good correlation between SFC and MC for the identification, enumeration and characterization of IMC in blood, based on large panels (>20) of antibody reagents., Peer reviewed