dataesr/scientific-paragraphs-categorization huggingface dataset:
5-to 7-fold), according to the RNA-seq results. Therefore, the target genes of MH_s15 were analyzed by using the IntaRNA software and the potential conserved interactive regions were shown in Table  S6 , but further experiments are needed to characterize the interactions between MH_s15 and its target genes and determine the influence of MH_s15 on the symbiosis between M. huakuii 7653R and host.
Prediction of sRNAs in the IGRs of M. huakuii 7653R The comparative analysis of IGRs was carried out among M. austrqalicum WSM2073, M. ciceri WSM1271, M. Loti MAFF303099, M. opportunistum WSM2075 and M. huakuii 7653R. Their genomic sequences and protein annotations were downloaded from the NCBI bacterial databases (ftp://ftp. ncbi. nih. gov/genomes/Bacteria). The predictions of sRNAs were performed as previously described  (del Val et al. , 2007). IGRs with a length ≥50 nt were scanned and homologous regions were clustered using WU-BLASTN (http://blast. wustl. edu) in the tested genomes with E-values ≤ 1e -5. The alignments were interrogated using eQRNA version 2. 0. 4 (ftp://ftp. genetics. wustl. edu/pub/eddy/software/qrna. tar. Z) as described previously  (del Val et al. , 2007). RNAz version 0.
1. 1 (http://www. tbi. univie. ac. at/∼wash/RNAz) was used to screen the conserved intergenic regions in these candidate genomic sequences, and overlapping sequences between eQRNA and RNAz were selected. Subsequently, pairwise alignments in both eQRNA and RNAz were calculated using RNAfold (ViennaRNA-2. 1. 1) to determine the stable secondary structures, with the stem-length options set to a minimum of 20 bp. The promoters and Rho-independent terminators were analyzed using Promoter 2. 0, RNAMotif and Erpin to further assess the resulting sequences. Finally, the nucleotide sequences of potential sRNAs were further inspected according to the results of RNA-seq deep sequencing. Each predicted sRNA was used to query the Rfam database to capture any annotated RNA regulatory elements.
Total purified RNA was then treated with tobacco acid pyrophosphatase (TAP) (2. 5 U/5 µg RNA in 50 µl for 2 h) to maintain the start regions of the transcription products. The quantity and quality of the processed RNA samples were assessed using of a NanoDrop ND-1000 spectrophotometer and Agilent 2100 Bioanalyzer. Qualified RNA was ligated to 5 ′ -and 3 ′ -RNA adapters by PCR, then the free adapters were removed and the remaining cDNA was purified. A Qubit R 2. 0 Fluorometer and Agilent2100 instrument were used to monitor the abundance and size of cDNA, respectively. Solexa sequencing was performed using an Illumina HiSeq 2500. After that, all sequencing data were mapped by using the genomic sequence of M. huakuii 7653R to obtain the effective reads.
Other Tools and Software Searches for promoters in the M. huakuii 7653R genome were performed using Promoter 2. 0 (http://www. cbs. dtu. dk/services/Promoter/) and BPROM 2. 4. 3. 1111 (http:// www. molquest. com/). Predictions of Rho-independent terminators were implemented with RNAMotif 3. 0. 7 (http:// casegroup. rutgers. edu/casegr-sh-2. 5. html), TransTermHP 2. 09 (transterm. cbcb. umd. edu/), FindTerm 2. 4. 3. 1111 (http:// www. molquest. com/) and Erpin 5. 4 (http://tagc. univ-mrs. fr/erpin/). Searches for known functional RNA sequences among the predicted sRNAs were conducted within the Rfam database using Rfam, version 12. 0 (http://rfam. xfam. org/ search)  (Nawrocki et al. , 2015). RNA secondary structures were analyzed using RNAfold 2. 1. 9 (http://rna. tbi. univie. ac. at/ cgi-bin/RNAWebSuite/RNAfold.
ACKNOWLEDGMENTS This work was supported by the funds from the  National Key Research and Development Program of China  (grant no. 2016YFD0100700 ), the  National Natural Science Foundation of China  (grant no. 31670243 ;  31371549 ;  31570844 ), the  Fundamental Research Funds for the Central Universities  ( 2016PY025  and  2011QC066 ), and the  Open Project of the State Key Laboratory of Agricultural Microbiology  (no. AMLKF2 01502 ).
Devices were sealed with a glass coverslip to minimize evaporation and placed on a temperature-controlled stage (37°C) of an inverted Zeiss Observer Z1 microscope equipped with a CCD camera (Photometrics CoolSNAP KINO) and a motorized stage. Images for timelapse sequences were acquired every 10 min for at least 12 h through a 20× air objective (0. 8 NA) using ZEN software (Zeiss). Images were analyzed using ZEN and ImageJ. Cell transit times through constrictions were measured for individual cells based on time-lapse sequences, with the starting point defined by the frame showing the first signs of nuclear deformation as a cell entered into a constriction, and the ending point defined by the frame at which the cell had migrated through the constriction and the nucleus was no longer "pinched.
Microscopy and analysis Unless otherwise noted, SAIM, TFM, confocal, and spheroid invasion assay imaging were performed on motorized total internal reflection fluorescence (TIRF) inverted microscopes (Ti-E Perfect Focus System; Nikon) controlled by MetaMorph (Molecular Devices) and Nikon Elements software and equipped with 488-, 561-, and 640nm lasers, 350/50 epifluorescence, a CSU-X1 spinning-disk confocal unit (Yokogawa Electric Company), electronic shutters, motorized stage, a scientific complementary metal-oxide-semiconductor (sC-MOS) camera (Zyla 5. 5 megapixel, Andor; or Orca Flash, Hamamatsu), and an electron-multiplying charge-coupled device (EMCCD) camera (QuantEM 512; Photometrics). Temperature and CO 2 were controlled by an environmental chamber and proportional integral derivative-controlled heater (In-Vivo Scientific).
Samples were imaged with 100×/1. 49 numerical aperture (NA) TIRF oilimmersion, 40×/1. 2 NA long-working-distance water-immersion, 20×/0. 75 NA air, and 10×/0. 45 NA air objectives. For live-cell imaging, phenol red-free growth medium with 10 mM 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid (HEPES; pH 7. 4) was used. For 3D imaging, confocal image slices were taken at 0. 2-or 1. 0-µm slices and the individual planes were maximum intensity z-projected for 2D visualization. Custom software packages for image analysis were written in Python, using ImageJ and the Eclipse Development Environment in Linux. Images were subject to a Gaussian blur of 1. 0 pixel to smooth background noise. Intensity and colocalization measurements of single confocal planes were calculated on a pixel-bypixel basis.
Single-cell invasion, acini and cell protrusions, and cell adhesion length were quantified manually and verified qualitatively across three independent experiments. Acini cross-sectional area was quantified with the free-hand selection tool in ImageJ. Focal adhesion lifetimes were quantified manually and verified qualitatively across three independent experiments. SAIM was performed as described  (Paszek et al. , 2012; Rubashkin et al. , 2014a) , using data analysis and 3D visualization programs written in Matlab and Python using libraries distributed by Enthought.
Microchannel migration assays Migration experiments in microfluidic devices were carried out as described previously  (Davidson et al. , 2014 (Davidson et al. , , 2015;; Denais et al. ,  as well as kinetic rates for binding and unbinding of molecular clutches. Monte Carlo simulations were executed using a Gillespie stochastic simulation algorithm  (Gillespie, 1977)  run on in-house simulation computers using Matlab (MathWorks, Natick, MA), version 2014b. For a detailed description of the simulation and relevant parameters, refer to the Supplemental Materials. The modified reinforcement model includes kinetic rates for addition of molecular clutches to the ensemble when a threshold force is reached by engaged clutches: K K n F F n n n add a dd,base clutch threshold clutch,max clutch clutch,max ( ) = × > × - where K add is a basal first-order clutch addition rate constant, F threshold is a threshold force for clutch reinforcement signaling, and n clutch,max represents the total number of available clutches in the cell.
06 N/m) cantilevers, which were calibrated by the thermal tune method. Force measurements were collected at multiple points across the surface of the gels and cells at a maximum trigger force of 2. 0 nN. The resulting force data were converted into elastic modulus using the Hertz Model program in IgorPro v6. 22A. Measurements were also repeated with pointed-tipped Asylum Research TR400PB silicon nitride (k = 0. 02 N/m) cantilevers, showing a similar trend. Surface plots were generated using the surf() function in Matlab. To determine cell elasticity, height cutoffs were chosen based on the height maps to assign pixel values associated with the cell versus the gel.
Micropipette aspiration Micropipette aspiration through 3-µm-wide, 5-µm-high channels was performed using microfluidic devices fabricated as described in  Denais et al. (2016). PDMS molds of the devices were filled with a 2% bovine serum albumin (BSA)/0. 2% FBS solution. Cells were trypsinized and resuspended in the 2% BSA/0. 2% FBS solution containing Hoechst 33342 for nuclear visualization. The cell suspension was perfused into the devices at constant pressure using a MCFS-EZ pressure controller (Fluigent). Channels were cleared by manual backflushing, and nuclear deformation of cells entering the channels was observed at 5 s intervals using a 20×/0. 4 NA phase contrast objective and Hamamatsu ORCA Flash 4. 0 V2 camera. Images were analyzed using a custom-written MATLAB algorithm.
Traction force microscopy Cells were seeded overnight on PA gels with 100-nm fluorescent red beads. Images of cells and beads were taken at 20× before adding 0. 01% SDS to lyse the cells from the surface. A second picture of the beads was taken afterward that was later aligned via the ImageJ (http://rsb. info. nih. gov/ij) registration plug-in StackReg. To assess bead movement, a particle image velocimetry (PIV) program was implemented in ImageJ as described previously  (Tseng et al. , 2012). The iterative scheme included a first pass at 32/64 (i. e. , interrogation and search window size in pixels), followed by a second pass at 16/32, all at a correlation threshold of 0. 60. Cross-correlation PIV was used for traction measurements on gels of different stiffness, with three iterative schemes of 128, 64, and 32 as the interrogation window sizes.
, 2003). In-line desalting was accomplished by using a reversed-phase trap column packed with Magic C 18 AQ (5-µm 200-Å resin; Michrom Bioresources, Auburn, CA), followed by peptide separations on a reversed-phase column packed with Magic resin and then directly mounted on the electrospray ion source. Data analysis was performed using Proteome Discoverer 1. 4 (Thermo Scientific, San Jose, CA). The data were searched against a Uniprot human database that included common contaminants. Sequest HT was used for database searching, and Percolator was used for scoring. Data acquired from the Orbitrap Elite were processed to generate normalized spectral count values for each protein. Similar to previously published techniques, each protein's spectral counts were divided by the total number of spectral counts for that sample and then divided by the protein's molecular weight  (Horton et al.
Human bioinformatics studies To analyze survival as a function of transcriptomic data in human breast cancer patients, we used an online tool (www. kmplot. com; Györffy et al. , 2013). The Affymetrix ID for paxillin was 201087_at. Briefly, the KMplot tool employs gene expression data and relapsefree and overall survival information from the Gene Expression Omnibus, the European Genome-Phenome Archive, and The Cancer Genome Atlas (TCGA) from >4000 patients. To analyze the effect of specific genes in survival, patient samples were split into two groups by predefined metrics for calculating quantile expression. Affymetrix transcriptome data for a user-selected probe were analyzed in KMplot by autoselecting the best cutoff of gene expression, computing the median of expression over the entire database, and analyzing all the prior step.
The cells were then added and incubated for at least 1 h at 37 °C before imaging. Images were taken using TIRF microscopy on an inverted microscope (Nikon TiE) with an Apo TIRF 100× oil objective lens, NA 1. 49 (Nikon). Data were acquired with a 200-ms exposure using either an EMCCD camera (Andor iXon) or an sCMOS camera (Hamamatsu Orca Flash). The no-load FRET efficiency and gamma factor (γ) were measured at the single-molecule level as described previously. To calculate FRET index (FRET i ), we divide the acceptor intensity, A (background subtracted), by the sum of the acceptor and donor (D) intensities (also background subtracted): FRET i = A/(A + D). Using the measured FRET index, we calculate the FRET efficiency (E), using the measured fraction of double-labeled sensor (α ≈ 0. 90): E FRET FRET FRET i i i α γ γ ( ) = - + We then convert from FRET efficiency, E, to an average force per sensor molecule at each pixel, using a previously measured calibration curve modified to incorporate the photophysical properties of the dyes used here  (Morimatsu et al.
, 2015). A detailed explanation of calculations of the average force per sensor and total force per cell was given previously  (Morimatsu et al. , 2015). Briefly, to measure the average force per sensor, we first segmented the images from the paxillin-eGFP signal or the FRET index signal. These images were normalized, boxcar averaged with a rotating reference frame, and then thresholded to create a binary mask. The binary mask was used for a watershed algorithm to isolate individual islands, which were then combined and indexed with custom-written MATLAB code with minimum adhesion size of 0. 5 µm 2. The average force per sensor was calculated by converting the FRET efficiency values to force values of individual pixels within the segmented regions. The total force per cell was calculated using FRET images of the entire cell taken on a Hamamatsu sCMOS camera.
Proteomics experiment and analysis The biotin ligase protocol was modified from the previously published method  (Roux et al. , 2012) , with some modifications outlined here. Four 10-cm dishes (∼20 million cells) of MCF10A MECs stably expressing BirA* constructs were cultured on tissue culture plastic and treated with TGFβ for 3 d. The cells were then incubated in medium supplemented with 50 µM biotin (B4639; Sigma-Aldrich) for 24 h before lysate collection. Cells were detached using trypsin-EDTA, washed three times with cold DPBS, and resuspended in 1. 6 ml of ice-cold RIPA buffer (50 mM Tris-HCl, pH 7. 5, 150 mM NaCl, 1 mM EDTA, 1 mM ethylene glycol tetraacetic acid, 0. 5% sodium deoxycholate, 0. 1% SDS, 1% NP-40) with protease inhibitor patient subtypes as long as they were lymph-node positive in the 2014 TCGA data set.
ACKNOWLEDGMENTS We thank  Micah Dembo  and  Qingzong Tseng  for providing TFM software and assistance,  Allan Bradley  for the hyperactive piggyBac transposase,  Harold Moses  for the PyMT Flox3 lines,  Zena Werb  for the Met1 cell line,  Lisa Jones  and the  Proteomics Facility at the Fred Hutchinson Cancer Research Center  for assistance with the protein identification studies, and  Eva Huang  and  Gabriela Lomeli  at  Stanford University  for assistance with the BioID assay and quantification. We thank members of the  Weaver, Dunn, Odde , and Lammerding groups for helpful discussions and technical insights. The trainee work was supported by a  Department of Defense National Defense Science and Engineering Graduate  Fellowship to M. G. R. , the  National Science Foundation Graduate Research Fellowship Program  to A.
After exclusion of common variants, both bothers carried a total of 121 identical missense heterozygous variants (none appearing as obvious candidate) and only five identical homozygous variants common to both brothers (Appendix Table  S1 ). Among these different genes, only the Chr4:57686748G>C SPINK2 variant was described to be predominantly expressed in human testis  (Appendix Fig S1A)  as well as in mouse testis  (Appendix Fig S1B). The mutation was validated by Sanger sequencing in both brothers (homozygous) and their parents (heterozygous) (Fig  2A ). SPINK2 thus appeared as the best candidate to explain the human condition. The variant Chr4:57686748G>C was not present in > 121,000 alleles analyzed in the ExAC database (http://exac. broadinstitute. org) and could have an effect on RNA splicing.
SPINK2 is located on chromosome 4 and contains four exons  (Fig 2B). The gene codes for a Kazal type 2 serine protease inhibitor also known as an acrosin-trypsin inhibitor. The Ensembl expression database (www. ensembl. org) predicts the presence of four transcripts. We studied the expression of the different transcripts in human testis by RT-PCR, and only one band was present corresponding to NM_021114, ENST00000248701, which codes for a protein of 9. 291 kDa consisting of 84 amino acids  (Fig 2C). All nucleotide sequences herein refer to this transcript. The identified mutation, c. 56-3C>G, is located three nucleotides before exon 2 and may create a new splice acceptor site, leading to a frameshift and premature stop codon in exon 2 and the generation of an abnormal transcript (T1) and/or to the skipping of exon 2 (44 nt) giving rise to an early stop codon at the beginning of exon 3 and the generation of another abnormal transcript (T2)  (Fig 2B).
Data represent mean AE SEM; the statistical difference was assessed with t-test, P-value as indicated. D Absence of Spink2 induces Golgi apparatus fragmentation and mislocalization. (D1, D2) IF experiments using an anti-Dpy19l2 antibody marking the specific NE facing the NDL (green staining) and an anti-GM130 antibody marking the cis-Golgi (red staining) show that the Golgi apparatus (GA) is a compact structure and located either in front of the NDL or close to it in WT round spermatids (normal). (D3-D6) In contrast, similar double staining of round spermatids from Spink2 À/À mice shows that only one-third of GA are compact and normally placed (D3) and the other GA are either displaced (D4), fragmented (D5), or both (D6). In panel (D6), white asterisk corresponds to a GA belonging to a different cell.
These observations in mice strongly support the notion that SPINK2 heterozygous mutations in man will impact spermatogenesis with a variable effect on fertility. We identified only one heterozygous mutation out of 611 analyzed patients indicating that SPINK2 variants are very rare, likely because heterozygous variants underwent a strong negative selection during evolution. This hypothesis is supported by data from the ExAC database which indicate that the SPINK2 gene has a high probability of loss of function intolerance (pLI = 0. 72). The testis is the organ which expresses the highest number of tissue-specific transcripts (n > 500)  (Feig et al, 2007; Dezso et al, 2008)  and altered spermatogenesis has been observed in knockout mouse models for more than 388 genes  (Massart et al, 2012).
Variants with a minor allele frequency > 5% in the NHLBI ESP6500 or in 1000 Genomes Project phase 1 datasets, or > 1% in ExAC, were discarded. We also compared these variants to an in-house database of 56 control exomes. All variants present in a homozygous state in this database were excluded. We used Variant Effect Predictor (VEP) to predict the impact of the selected variants. We only retained variants impacting splice donor/acceptor sites or EMBO Molecular Medicine Vol 9 | No 8 | 2017 ª 2017 The Authors.
EMBO Molecular Medicine Mutations in SPINK2 induce azoospermia Zine-Eddine Kherraf et al causing frameshift, in-frame insertions/deletions, stop gain, stop loss, or missense variants except those scored as "tolerated" by SIFT (sift. jcvi. org) and as "benign" by PolyPhen-2 (genetics. bwh. harva rd. edu/pph2). All steps from sequence mapping to variant selection were performed using the ExSQLibur pipeline (https://github. com/ tkaraouzene/ExSQLibur). Our datasets were obtained from subjects who have consented to the use of their individual genetic data for biomedical research, but not for unlimited public data release. Therefore, we submitted it to the European Genome-phenome Archive, through which researchers can apply for access of the raw data under the accession number EGAD00001003326.
Sanger sequencing Sanger sequencing of the four SPINK2 exons and intron borders was carried out using the primers described in Appendix Table  S3. Thirtyfive cycles of PCR amplification were carried out with a hybridization temperature of 60°C. Sequencing reactions were performed using BigDye Terminator v3. 1 (Applied Biosystems). Sequence analyses were carried out on ABI 3130XL (Applied Biosystems). Sequences were analyzed using seqscape software (Applied Biosystems).
Primary antibodies SPINK2 rabbit polyclonal antibody was from Sigma-Aldrich (HPA026813) and used at 1/1,000 for Western blot analysis. Sperm protein Sp56 and Golgi matrix protein GM130 (610822) mouse monoclonal antibodies were from QED Bioscience Inc. (used at 1/800 and 1/200, respectively). Promyelocytic leukemia zinc finger protein PLZF rabbit polyclonal antibody (Sc-22839) was from Santa Cruz Biotechnology. Dpy19l2 antibodies were produced in rabbit as polyclonal antibodies raised against RSKLREGSSDRPQSSC and CTGQARRRWSAATMEP peptides corresponding to amino acids 6-21 and 21-36 of the N-terminus of mouse Dpy19l2  (Pierre et al, 2012). DDK antibody was from OriGene (TA50011) or Sigma-Aldrich (FLAG â M2F1804) and used at 1/10,000 for Western blot analysis. Acrosin antibody was previously described  (Gallo et al, 1991)  and is a gift from Denise Escalier.
Ultrathin sections of the samples were cut with an ultramicrotome (Leica), and the sections were post-stained with 5% uranyl acetate and 0. 4% lead citrate before being observed with an electron microscope at 80 kV (JEOL 1200EX). Images were acquired with a digital camera (Veleta; SIS, Olympus), and morphometric analysis was performed with iTEM software (Olympus).
Statistical analyses n represents the number of biological replicates. For sperm analyses, for each replicate, more than 100 sperm were assessed per condition. Statistical analyses were performed with SigmaPlot 10 and GraphPad Prism 7. t-Tests were used to compare WT and KO samples. Data represent mean AE SEM or SD, as indicated. Statistical tests with a two-tailed P-value ≤ 0. 05 were considered significant. Expanded View for this article is available online. The paper explained Problem Infertility concerns one in seven couples and is usually addressed by performing in vitro fertilization (IVF) often by injecting spermatozoa directly into the oocytes by intracytoplasmic sperm injection (ICSI). Some men have a non-obstructive azoospermia (NOA), caused by a deficient spermatogenesis, and have no spermatozoa in the ejaculate.
Acknowledgements We thank the GIN electron microscopy platform and  Anne Bertrand , and the IAB microscopy platform and  Alexei Grichine  and  Jacques Mazzega  for their technical help. We thank  Myriam Dridi  for her work on HEK cells and antibody validation,  Jean Pascal Hograindleur  for his help for CASA experiments and  Denise Escalier  for her generous gift of human anti-acrosin antibody. This work was mainly supported by the  French research agency (ANR)  within the  2009 Genopat program  for the  ICG2I  project " Identification and characterization of genetic causes of male infertility " to PR and CA. Support was also obtained from the  Fondation Maladies Rares (FMR)  for the project  R16070CC , "Identification of genetic causes of human NOA ".