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  • 1. Bengtsson-Palme, Johan
    et al.
    Angelin, Martin
    Huss, Mikael
    Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics. Stockholm University, Science for Life Laboratory (SciLifeLab).
    Kjellqvist, Sanela
    Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics. Stockholm University, Science for Life Laboratory (SciLifeLab).
    Kristiansson, Erik
    Palmgren, Helena
    Larsson, D. G. Joakim
    Johansson, Anders
    The Human Gut Microbiome as a Transporter of Antibiotic Resistance Genes between Continents2015In: Antimicrobial Agents and Chemotherapy, ISSN 0066-4804, E-ISSN 1098-6596, Vol. 59, no 10, p. 6551-6560Article in journal (Refereed)
    Abstract [en]

    Previous studies of antibiotic resistance dissemination by travel have, by targeting only a select number of cultivable bacterial species, omitted most of the human microbiome. Here, we used explorative shotgun metagenomic sequencing to address the abundance of >300 antibiotic resistance genes in fecal specimens from 35 Swedish students taken before and after exchange programs on the Indian peninsula or in Central Africa. All specimens were additionally cultured for extended-spectrum beta-lactamase (ESBL)-producing enterobacteria, and the isolates obtained were genome sequenced. The overall taxonomic diversity and composition of the gut microbiome remained stable before and after travel, but there was an increasing abundance of Proteobacteria in 25/35 students. The relative abundance of antibiotic resistance genes increased, most prominently for genes encoding resistance to sulfonamide (2.6-fold increase), trimethoprim (7.7-fold), and beta-lactams (2.6-fold). Importantly, the increase observed occurred without any antibiotic intake. Of 18 students visiting the Indian peninsula, 12 acquired ESBL-producing Escherichia coli, while none returning from Africa were positive. Despite deep sequencing efforts, the sensitivity of metagenomics was not sufficient to detect acquisition of the low-abundant genes responsible for the observed ESBL phenotype. In conclusion, metagenomic sequencing of the intestinal microbiome of Swedish students returning from exchange programs in Central Africa or the Indian peninsula showed increased abundance of genes encoding resistance to widely used antibiotics.

  • 2. Branca, Rui M. M.
    et al.
    Orre, Lukas M.
    Johansson, Henrik J.
    Granholm, Viktor
    Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics. Stockholm University, Science for Life Laboratory (SciLifeLab).
    Huss, Mikael
    Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics. Stockholm University, Science for Life Laboratory (SciLifeLab).
    Perez-Bercoff, Åsa
    Forshed, Jenny
    Käll, Lukas
    Lehtio, Janne
    HiRIEF LC-MSMS enables deep proteome coverage and unbiased proteogenomics2014In: Nature Methods, ISSN 1548-7091, E-ISSN 1548-7105, Vol. 11, no 1, p. 59-+Article in journal (Refereed)
    Abstract [en]

    We present a liquid chromatography-mass spectrometry (LC-MSMS)-based method permitting unbiased (gene prediction-independent) genome-wide discovery of protein-coding loci in higher eukaryotes. Using high-resolution isoelectric focusing (HiRIEF) at the peptide level in the 3.7-5.0 pH range and accurate peptide isoelectric point (pI) prediction, we probed the six-reading-frame translation of the human and mouse genomes and identified 98 and 52 previously undiscovered protein-coding loci, respectively. The method also enabled deep proteome coverage, identifying 13,078 human and 10,637 mouse proteins.

  • 3. Brownstein, Catherine A.
    et al.
    Beggs, Alan H.
    Homer, Nils
    Merriman, Barry
    Yu, Timothy W.
    Flannery, Katherine C.
    DeChene, Elizabeth T.
    Towne, Meghan C.
    Savage, Sarah K.
    Price, Emily N.
    Holm, Ingrid A.
    Luquette, Lovelace J.
    Lyon, Elaine
    Majzoub, Joseph
    Neupert, Peter
    McCallie, David, Jr.
    Szolovits, Peter
    Willard, Huntington F.
    Mendelsohn, Nancy J.
    Temme, Renee
    Finkel, Richard S.
    Yum, Sabrina W.
    Medne, Livija
    Sunyaev, Shamil R.
    Adzhubey, Ivan
    Cassa, Christopher A.
    de Bakker, Paul I. W.
    Duzkale, Hatice
    Dworzynski, Piotr
    Fairbrother, William
    Francioli, Laurent
    Funke, Birgit H.
    Giovanni, Monica A.
    Handsaker, Robert E.
    Lage, Kasper
    Lebo, Matthew S.
    Lek, Monkol
    Leshchiner, Ignaty
    MacArthur, Daniel G.
    McLaughlin, Heather M.
    Murray, Michael F.
    Pers, Tune H.
    Polak, Paz P.
    Raychaudhuri, Soumya
    Rehm, Heidi L.
    Soemedi, Rachel
    Stitziel, Nathan O.
    Vestecka, Sara
    Supper, Jochen
    Gugenmus, Claudia
    Klocke, Bernward
    Hahn, Alexander
    Schubach, Max
    Menzel, Mortiz
    Biskup, Saskia
    Freisinger, Peter
    Deng, Mario
    Braun, Martin
    Perner, Sven
    Smith, Richard J. H.
    Andorf, Janeen L.
    Huang, Jian
    Ryckman, Kelli
    Sheffield, Val C.
    Stone, Edwin M.
    Bair, Thomas
    Black-Ziegelbein, E. Ann
    Braun, Terry A.
    Darbro, Benjamin
    DeLuca, Adam P.
    Kolbe, Diana L.
    Scheetz, Todd E.
    Shearer, Aiden E.
    Sompallae, Rama
    Wang, Kai
    Bassuk, Alexander G.
    Edens, Erik
    Mathews, Katherine
    Moore, Steven A.
    Shchelochkov, Oleg A.
    Trapane, Pamela
    Bossler, Aaron
    Campbell, Colleen A.
    Heusel, Jonathan W.
    Kwitek, Anne
    Maga, Tara
    Panzer, Karin
    Wassink, Thomas
    Van Daele, Douglas
    Azaiez, Hela
    Booth, Kevin
    Meyer, Nic
    Segal, Michael M.
    Williams, Marc S.
    Tromp, Gerard
    White, Peter
    Corsmeier, Donald
    Fitzgerald-Butt, Sara
    Herman, Gail
    Lamb-Thrush, Devon
    McBride, Kim L.
    Newsom, David
    Pierson, Christopher R.
    Rakowsky, Alexander T.
    Maver, Ales
    Lovrecic, Luca
    Palandacic, Anja
    Peterlin, Borut
    Torkamani, Ali
    Wedell, Anna
    Huss, Mikael
    Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics.
    Alexeyenko, Andrey
    Lindvall, Jessica M.
    Magnusson, Mans
    Nilsson, Daniel
    Stranneheim, Henrik
    Taylan, Fulya
    Gilissen, Christian
    Hoischen, Alexander
    van Bon, Bregje
    Yntema, Helger
    Nelen, Marcel
    Zhang, Weidong
    Sager, Jason
    Zhang, Lu
    Blair, Kathryn
    Kural, Deniz
    Cariaso, Michael
    Lennon, Greg G.
    Javed, Asif
    Agrawal, Saloni
    Ng, Pauline C.
    Sandhu, Komal S.
    Krishna, Shuba
    Veeramachaneni, Vamsi
    Isakov, Ofer
    Halperin, Eran
    Friedman, Eitan
    Shomron, Noam
    Glusman, Gustavo
    Roach, Jared C.
    Caballero, Juan
    Cox, Hannah C.
    Mauldin, Denise
    Ament, Seth A.
    Rowen, Lee
    Richards, Daniel R.
    San Lucas, F. Anthony
    Gonzalez-Garay, Manuel L.
    Caskey, C. Thomas
    Bai, Yu
    Huang, Ying
    Fang, Fang
    Zhang, Yan
    Wang, Zhengyuan
    Barrera, Jorge
    Garcia-Lobo, Juan M.
    Gonzalez-Lamuno, Domingo
    Llorca, Javier
    Rodriguez, Maria C.
    Varela, Ignacio
    Reese, Martin G.
    De la Vega, Francisco M.
    Kiruluta, Edward
    Cargill, Michele
    Hart, Reece K.
    Sorenson, Jon M.
    Lyon, Gholson J.
    Stevenson, David A.
    Bray, Bruce E.
    Moore, Barry M.
    Eilbeck, Karen
    Yandell, Mark
    Zhao, Hongyu
    Hou, Lin
    Chen, Xiaowei
    Yan, Xiting
    Chen, Mengjie
    Li, Cong
    Yang, Can
    Gunel, Murat
    Li, Peining
    Kong, Yong
    Alexander, Austin C.
    Albertyn, Zayed I.
    Boycott, Kym M.
    Bulman, Dennis E.
    Gordon, Paul M. K.
    Innes, A. Micheil
    Knoppers, Bartha M.
    Majewski, Jacek
    Marshall, Christian R.
    Parboosingh, Jillian S.
    Sawyer, Sarah L.
    Samuels, Mark E.
    Schwartzentruber, Jeremy
    Kohane, Isaac S.
    Margulies, David M.
    An international effort towards developing standards for best practices in analysis, interpretation and reporting of clinical genome sequencing results in the CLARITY Challenge2014In: Genome Biology, ISSN 1465-6906, E-ISSN 1474-760X, Vol. 15, no 3, article id R53Article in journal (Refereed)
    Abstract [en]

    Background: There is tremendous potential for genome sequencing to improve clinical diagnosis and care once it becomes routinely accessible, but this will require formalizing research methods into clinical best practices in the areas of sequence data generation, analysis, interpretation and reporting. The CLARITY Challenge was designed to spur convergence in methods for diagnosing genetic disease starting from clinical case history and genome sequencing data. DNA samples were obtained from three families with heritable genetic disorders and genomic sequence data were donated by sequencing platform vendors. The challenge was to analyze and interpret these data with the goals of identifying disease-causing variants and reporting the findings in a clinically useful format. Participating contestant groups were solicited broadly, and an independent panel of judges evaluated their performance. Results: A total of 30 international groups were engaged. The entries reveal a general convergence of practices on most elements of the analysis and interpretation process. However, even given this commonality of approach, only two groups identified the consensus candidate variants in all disease cases, demonstrating a need for consistent fine-tuning of the generally accepted methods. There was greater diversity of the final clinical report content and in the patient consenting process, demonstrating that these areas require additional exploration and standardization. Conclusions: The CLARITY Challenge provides a comprehensive assessment of current practices for using genome sequencing to diagnose and report genetic diseases. There is remarkable convergence in bioinformatic techniques, but medical interpretation and reporting are areas that require further development by many groups.

  • 4. Danielsson, Frida
    et al.
    James, Tojo
    Gomez-Cabrero, David
    Huss, Mikael
    Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics. Stockholm University, Science for Life Laboratory (SciLifeLab).
    Assessing the consistency of public human tissue RNA-seq data sets2015In: Briefings in Bioinformatics, ISSN 1467-5463, E-ISSN 1477-4054, Vol. 16, no 6, p. 941-949Article in journal (Refereed)
    Abstract [en]

    Sequencing-based gene expression methods like RNA-sequencing (RNA-seq) have become increasingly common, but it is often claimed that results obtained in different studies are not comparable owing to the influence of laboratory batch effects, differences in RNA extraction and sequencing library preparation methods and bioinformatics processing pipelines. It would be unfortunate if different experiments were in fact incomparable, as there is great promise in data fusion and meta-analysis applied to sequencing data sets. We therefore compared reported gene expression measurements for ostensibly similar samples (specifically, human brain, heart and kidney samples) in several different RNA-seq studies to assess their overall consistency and to examine the factors contributing most to systematic differences. The same comparisons were also performed after preprocessing all data in a consistent way, eliminating potential bias from bioinformatics pipelines. We conclude that published human tissue RNA-seq expression measurements appear relatively consistent in the sense that samples cluster by tissue rather than laboratory of origin given simple preprocessing transformations. The article is supplemented by a detailed walkthrough with embedded R code and figures.

  • 5. Hagey, Daniel W.
    et al.
    Zaouter, Cecile
    Combeau, Gaelle
    Andersson Lendahl, Monika
    Andersson, Olov
    Huss, Mikael
    Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics. Stockholm University, Science for Life Laboratory (SciLifeLab).
    Muhr, Jonas
    Distinct transcription factor complexes act on a permissive chromatin landscape to establish regionalized gene expression in CNS stem cells2016In: Genome Research, ISSN 1088-9051, E-ISSN 1549-5469, Vol. 26, no 7, p. 908-917Article in journal (Refereed)
    Abstract [en]

    Spatially distinct gene expression profiles in neural stem cells (NSCs) are a prerequisite to the formation of neuronal diversity, but how these arise from the regulatory interactions between chromatin accessibility and transcription factor activity has remained unclear. Here, we demonstrate that, despite their distinct gene expression profiles, NSCs of the mouse cortex and spinal cord share the majority of their DNase I hypersensitive sites (DHSs). Regardless of this similarity, domain-specific gene expression is highly correlated with the relative accessibility of associated DHSs, as determined by sequence read density. Notably, the binding pattern of the general NSC transcription factor SOX2 is also largely cell type specific and coincides with an enrichment of LHX2 motifs in the cortex and HOXA9 motifs in the spinal cord. Interestingly, in a zebrafish reporter gene system, these motifs were critical determinants of patterned gene expression along the rostral-caudal axis. Our findings establish a predictive model for patterned NSC gene expression, whereby domain-specific expression of LHX2 and HOX proteins act on their target motifs within commonly accessible cis-regulatory regions to specify SOX2 binding. In turn, this binding correlates strongly with these DHSs relative accessibility-a robust predictor of neighboring gene expression.

  • 6. Hasmats, Johanna
    et al.
    Green, Henrik
    Solnestam, Beata Werne
    Zajac, Pawel
    Huss, Mikael
    Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics.
    Orear, Cedric
    Validire, Pierre
    Bjursell, Magnus
    Lundeberg, Joakim
    Validation of whole genome amplification for analysis of the p53 tumor suppressor gene in limited amounts of tumor samples2012In: Biochemical and Biophysical Research Communications - BBRC, ISSN 0006-291X, E-ISSN 1090-2104, Vol. 425, no 2, p. 379-383Article in journal (Refereed)
    Abstract [en]

    Personalized cancer treatment requires molecular characterization of individual tumor biopsies. These samples are frequently only available in limited quantities hampering genomic analysis. Several whole genome amplification (WGA) protocols have been developed with reported varying representation of genomic regions post amplification. In this study we investigate region dropout using a 929 polymerase based WGA approach. DNA from 123 lung cancers specimens and corresponding normal tissue were used and evaluated by Sanger sequencing of the p53 exons 5-8. To enable comparative analysis of this scarce material, WGA samples were compared with unamplified material using a pooling strategy of the 123 samples. In addition, a more detailed analysis of exon 7 amplicons were performed followed by extensive cloning and Sanger sequencing. Interestingly, by comparing data from the pooled samples to the individually sequenced exon 7, we demonstrate that mutations are more easily recovered from WGA pools and this was also supported by simulations of different sequencing coverage. Overall this data indicate a limited random loss of genomic regions supporting the use of whole genome amplification for genomic analysis.

  • 7. Hasmats, Johanna
    et al.
    Gréen, Henrik
    Orear, Cedric
    Validire, Pierre
    Huss, Mikael
    Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics. Stockholm University, Science for Life Laboratory (SciLifeLab).
    Käller, Max
    Lundeberg, Joakim
    Assessment of Whole Genome Amplification for Sequence Capture and Massively Parallel Sequencing2014In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 9, no 1, article id e84785Article in journal (Refereed)
    Abstract [en]

    Exome sequence capture and massively parallel sequencing can be combined to achieve inexpensive and rapid global analyses of the functional sections of the genome. The difficulties of working with relatively small quantities of genetic material, as may be necessary when sharing tumor biopsies between collaborators for instance, can be overcome using whole genome amplification. However, the potential drawbacks of using a whole genome amplification technology based on random primers in combination with sequence capture followed by massively parallel sequencing have not yet been examined in detail, especially in the context of mutation discovery in tumor material. In this work, we compare mutations detected in sequence data for unamplified DNA, whole genome amplified DNA, and RNA originating from the same tumor tissue samples from 16 patients diagnosed with non-small cell lung cancer. The results obtained provide a comprehensive overview of the merits of these techniques for mutation analysis. We evaluated the identified genetic variants, and found that most (74%) of them were observed in both the amplified and the unamplified sequence data. Eighty-nine percent of the variations found by WGA were shared with unamplified DNA. We demonstrate a strategy for avoiding allelic bias by including RNA-sequencing information.

  • 8. Holme, Petter
    et al.
    Huss, Mikael
    Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics.
    Understanding and Exploiting Information Spreading and Integrating Technologies2011In: Journal of Computer Science and Technology, ISSN 1000-9000, E-ISSN 1860-4749, Vol. 26, no 5, p. 829-836Article in journal (Refereed)
    Abstract [en]

    Our daily life leaves an increasing amount of digital traces, footprints that are improving our lives. Data-mining tools, like recommender systems, convert these traces to information for aiding decisions in an ever-increasing number of areas in our lives. The feedback loop from what we do, to the information this produces, to decisions what to do next, will likely be an increasingly important factor in human behavior on all levels from individuals to societies. In this essay, we review some effects of this feedback and discuss how to understand and exploit them beyond mapping them on more well-understood phenomena. We take examples from models of spreading phenomena in social media to argue that analogies can be deceptive, instead we need to fresh approaches to the new types of data, something we exemplify with promising applications in medicine.

  • 9. Holme, Petter
    et al.
    Huss, Mikael
    Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics.
    Lee, Sang Hoon
    Atmospheric Reaction Systems as Null-Models to Identify Structural Traces of Evolution in Metabolism2011In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 6, no 5, p. e19759-Article in journal (Refereed)
    Abstract [en]

    The metabolism is the motor behind the biological complexity of an organism. One problem of characterizing its large-scale structure is that it is hard to know what to compare it to. All chemical reaction systems are shaped by the same physics that gives molecules their stability and affinity to react. These fundamental factors cannot be captured by standard null-models based on randomization. The unique property of organismal metabolism is that it is controlled, to some extent, by an enzymatic machinery that is subject to evolution. In this paper, we explore the possibility that reaction systems of planetary atmospheres can serve as a null-model against which we can define metabolic structure and trace the influence of evolution. We find that the two types of data can be distinguished by their respective degree distributions. This is especially clear when looking at the degree distribution of the reaction network (of reaction connected to each other if they involve the same molecular species). For the Earth's atmospheric network and the human metabolic network, we look into more detail for an underlying explanation of this deviation. However, we cannot pinpoint a single cause of the difference, rather there are several concurrent factors. By examining quantities relating to the modular-functional organization of the metabolism, we confirm that metabolic networks have a more complex modular organization than the atmospheric networks, but not much more. We interpret the more variegated modular arrangement of metabolism as a trace of evolved functionality. On the other hand, it is quite remarkable how similar the structures of these two types of networks are, which emphasizes that the constraints from the chemical properties of the molecules has a larger influence in shaping the reaction system than does natural selection.

  • 10. James, Tojo
    et al.
    Lindén, Magdalena
    Morikawa, Hiromasa
    Fernandes, Sunjay Jude
    Ruhrmann, Sabrina
    Huss, Mikael
    Stockholm University, Science for Life Laboratory (SciLifeLab). Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics.
    Brandi, Maya
    Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics. Stockholm University, Science for Life Laboratory (SciLifeLab).
    Piehl, Fredrik
    Jagodic, Maja
    Tegnér, Jesper
    Khademi, Mohsen
    Olsson, Tomas
    Gomez-Cabrero, David
    Kockum, Ingrid
    Impact of genetic risk loci for multiple sclerosis on expression of proximal genes in patients2018In: Human Molecular Genetics, ISSN 0964-6906, E-ISSN 1460-2083, Vol. 27, no 5, p. 912-928Article in journal (Refereed)
    Abstract [en]

    Despite advancements in genetic studies, it is difficult to understand and characterize the functional relevance of disease-associated genetic variants, especially in the context of a complex multifactorial disease such as multiple sclerosis (MS). As a large proportion of expression quantitative trait loci (eQTLs) are context-specific, we performed RNA-Seq in peripheral blood mononuclear cells from MS patients (n = 145) to identify eQTLs in regions centered on 109 MS risk single nucleotide polymorphisms and 7 associated human leukocyte antigen variants. We identified 77 statistically significant eQTL associations, including pseudogenes and non-coding RNAs. Thirty-eight out of 40 testable eQTL effects were colocalized with the disease association signal. As many eQTLs are tissue specific, we aimed to detail their significance in different cell types. Approximately 70% of the eQTLs were replicated and characterized in at least one major peripheral blood mononuclear cell-derived cell type. Furthermore, 40% of eQTLs were found to be more pronounced in MS patients compared with non-inflammatory neurological diseases patients. In addition, we found two single nucleotide polymorphisms to be significantly associated with the proportions of three different cell types. Mapping to enhancer histone marks and predicted transcription factor binding sites added additional functional evidence for eight eQTL regions. As an example, we found that rs71624119, shared with three other autoimmune diseases and located in a primed enhancer (H3K4me1) with potential binding for STAT transcription factors, significantly associates with ANKRD55 expression. This study provides many novel and validated targets for future functional characterization of MS and other diseases.

  • 11. Johansson, Henrik J.
    et al.
    Socciarelli, Fabio
    Vacanti, Nathaniel M.
    Haugen, Mads H.
    Zhu, Yafeng
    Siavelis, Ioannis
    Fernandez-Woodbridge, Alejandro
    Aure, Miriam R.
    Sennblad, Bengt
    Vesterlund, Mattias
    Branca, Rui M.
    Orre, Lukas M.
    Huss, Mikael
    Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics. Stockholm University, Science for Life Laboratory (SciLifeLab).
    Fredlund, Erik
    Beraki, Elsa
    Garred, Øystein
    Boekel, Jorrit
    Sauer, Torill
    Zhao, Wei
    Nord, Silje
    Höglander, Elen K.
    Jans, Daniel C.
    Brismar, Hjalmar
    Haukaas, Tonje H.
    Bathen, Tone F.
    Schlichting, Ellen
    Naume, Bjørn
    Geisler, Jürgen
    Hofvind, Solveig
    Engebråten, Olav
    Aarum Geitvik, Gry
    Langerød, Anita
    Kåresen, Rolf
    Mælandsmo, Gunhild Mari
    Sørlie, Therese
    Skjerven, Helle Kristine
    Park, Dæhoon
    Hartman-Johnsen, Olaf-Johan
    Luders, Torben
    Borgen, Elin
    Kristensen, Vessela N.
    Russnes, Hege G.
    Lingjærde, Ole Christian
    Mills, Gordon B.
    Sahlberg, Kristine K.
    Børresen-Dale, Anne-Lise
    Lehtiö, Janne
    Breast cancer quantitative proteome and proteogenomic landscape2019In: Nature Communications, ISSN 2041-1723, E-ISSN 2041-1723, Vol. 10, article id 1600Article in journal (Refereed)
    Abstract [en]

    In the preceding decades, molecular characterization has revolutionized breast cancer (BC) research and therapeutic approaches. Presented herein, an unbiased analysis of breast tumor proteomes, inclusive of 9995 proteins quantified across all tumors, for the first time recapitulates BC subtypes. Additionally, poor-prognosis basal-like and luminal B tumors are further subdivided by immune component infiltration, suggesting the current classification is incomplete. Proteome-based networks distinguish functional protein modules for breast tumor groups, with co-expression of EGFR and MET marking ductal carcinoma in situ regions of normal-like tumors and lending to a more accurate classification of this poorly defined subtype. Genes included within prognostic mRNA panels have significantly higher than average mRNA-protein correlations, and gene copy number alterations are dampened at the protein-level; underscoring the value of proteome quantification for prognostication and phenotypic classification. Furthermore, protein products mapping to non-coding genomic regions are identified; highlighting a potential new class of tumor-specific immunotherapeutic targets.

  • 12. Lindholm, Malene E.
    et al.
    Huss, Mikael
    Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics.
    Solnestam, Beata W.
    Kjellqvist, Sanela
    Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics.
    Lundeberg, Joakim
    Sundberg, Carl J.
    The human skeletal muscle transcriptome: sex differences, alternative splicing, and tissue homogeneity assessed with RNA sequencing2014In: The FASEB Journal, ISSN 0892-6638, E-ISSN 1530-6860, Vol. 28, no 10, p. 4571-4581Article in journal (Refereed)
    Abstract [en]

    Human skeletal muscle health is important for quality of life and several chronic diseases, including type II diabetes, heart disease, and cancer. Skeletal muscle is a tissue widely used to study mechanisms behind different diseases and adaptive effects of controlled interventions. For such mechanistic studies, knowledge about the gene expression profiles in different states is essential. Since the baseline transcriptome has not been analyzed systematically, the purpose of this study was to provide a deep reference profile of female and male skeletal muscle. RNA sequencing data were analyzed from a large set of 45 resting human muscle biopsies. We provide extensive information on the skeletal muscle transcriptome, including 5 previously unannotated protein-coding transcripts. Global transcriptional tissue homogeneity was strikingly high, within both a specific muscle and the contralateral leg. We identified >23,000 known isoforms and found >5000 isoforms that differ between the sexes. The female and male transcriptome was enriched for genes associated with oxidative metabolism and protein catabolic processes, respectively. The data demonstrate remarkably high tissue homogeneity and provide a deep and extensive baseline reference for the human skeletal muscle transcriptome, with regard to alternative splicing, novel transcripts, and sex differences in functional ontology.

  • 13. Lindskog, Cecilia
    et al.
    Linne, Jerker
    Fagerberg, Linn
    Hallström, Björn M.
    Sundberg, Carl Johan
    Lindholm, Malene
    Huss, Mikael
    Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics. Stockholm University, Science for Life Laboratory (SciLifeLab).
    Kampf, Caroline
    Choi, Howard
    Liem, David A.
    Ping, Peipei
    Varemo, Leif
    Mardinoglu, Adil
    Nielsen, Jens
    Larsson, Erik
    Ponten, Fredrik
    Uhlen, Mathias
    The human cardiac and skeletal muscle proteomes defined by transcriptomics and antibody-based profiling2015In: BMC Genomics, ISSN 1471-2164, E-ISSN 1471-2164, Vol. 16, article id 475Article in journal (Refereed)
    Abstract [en]

    Background: To understand cardiac and skeletal muscle function, it is important to define and explore their molecular constituents and also to identify similarities and differences in the gene expression in these two different striated muscle tissues. Here, we have investigated the genes and proteins with elevated expression in cardiac and skeletal muscle in relation to all other major human tissues and organs using a global transcriptomics analysis complemented with antibody-based profiling to localize the corresponding proteins on a single cell level. Results: Our study identified a comprehensive list of genes expressed in cardiac and skeletal muscle. The genes with elevated expression were further stratified according to their global expression pattern across the human body as well as their precise localization in the muscle tissues. The functions of the proteins encoded by the elevated genes are well in line with the physiological functions of cardiac and skeletal muscle, such as contraction, ion transport, regulation of membrane potential and actomyosin structure organization. A large fraction of the transcripts in both cardiac and skeletal muscle correspond to mitochondrial proteins involved in energy metabolism, which demonstrates the extreme specialization of these muscle tissues to provide energy for contraction. Conclusions: Our results provide a comprehensive list of genes and proteins elevated in striated muscles. A number of proteins not previously characterized in cardiac and skeletal muscle were identified and localized to specific cellular subcompartments. These proteins represent an interesting starting point for further functional analysis of their role in muscle biology and disease.

  • 14. Lundmark, Anna
    et al.
    Hu, Yue O. O.
    Huss, Mikael
    Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics. Stockholm University, Science for Life Laboratory (SciLifeLab).
    Johannsen, Gunnar
    Andersson, Anders F.
    Yucel-Lindberg, Tülay
    Identification of Salivary Microbiota and Its Association With Host Inflammatory Mediators in Periodontitis2019In: Frontiers in Cellular and Infection Microbiology, E-ISSN 2235-2988, Vol. 9, article id 216Article in journal (Refereed)
    Abstract [en]

    Periodontitis is a microbial-induced chronic inflammatory disease, which may not only result in tooth loss, but can also contribute to the development of various systemic diseases. The transition from healthy to diseased periodontium depends on microbial dysbiosis and impaired host immune response. Although periodontitis is a common disease as well as associated with various systemic inflammatory conditions, the taxonomic profiling of the salivary microbiota in periodontitis and its association with host immune and inflammatory mediators has not been reported. Therefore, the aim of this study was to identify key pathogens and their potential interaction with the host's inflammatory mediators in saliva samples for periodontitis risk assessment. The microbial 16S rRNA gene sequencing and the levels of inflammatory mediators were performed in saliva samples from patients with chronic periodontitis and periodontally healthy control subjects. The salivary microbial community composition differed significantly between patients with chronic periodontitis and healthy controls. Our analyses identified a number of microbes, including bacteria assigned to Eubacterium saphenum, Tannerella forsythia, Filifactor alocis, Streptococcus mitis/parasanguinis, Parvimonas micra, Prevotella sp., Phocaeicola sp., and Fretibacterium sp. as more abundant in periodontitis, compared to healthy controls. In samples from healthy individuals, we identified Campylobacter concisus, and Veillonella sp. as more abundant. Integrative analysis of the microbiota and inflammatory mediators/cytokines revealed associations that included positive correlations between the pathogens Treponema sp. and Selenomas sp. and the cytokines chitinase 3-like 1, sIL-6R alpha, sTNF-R1, and gp 130/sIL-6R beta. In addition, a negative correlation was identified between IL-10 and Filifactor alocis. Our results reveal distinct and disease-specific patterns of salivary microbial composition between patients with periodontitis and healthy controls, as well as significant correlations between microbiota and host-mediated inflammatory cytokines. The positive correlations between the pathogens Treponema sp. and Selenomas sp. and the cytokines chitinase 3-like 1, sIL-6R alpha, sTNF-R1, and gp 130/sIL-6R beta might have the future potential to serve as a combined bacteria-host salivary biomarker panel for diagnosis of the chronic infectious disease periodontitis. However, further studies are required to determine the capacity of these microbes and inflammatory mediators as a salivary biomarker panel for periodontitis.

  • 15. Ma, Yuanjun
    et al.
    Miao, Yali
    Peng, Zhuochun
    Sandgren, Johanna
    De Stahl, Teresita Diaz
    Huss, Mikael
    Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics. Stockholm University, Science for Life Laboratory (SciLifeLab).
    Lennartsson, Lena
    Liu, Yanling
    Nister, Monica
    Nilsson, Sten
    Li, Chunde
    Identification of mutations, gene expression changes and fusion transcripts by whole transcriptome RNAseq in docetaxel resistant prostate cancer cells2016In: SpringerPlus, E-ISSN 2193-1801, Vol. 5, article id 1861Article in journal (Refereed)
    Abstract [en]

    Docetaxel has been the standard first-line therapy in metastatic castration resistant prostate cancer. The survival benefit is, however, limited by either primary or acquired resistance. In this study, Du145 prostate cancer cells were converted to docetaxel-resistant cells Du145-R and Du145-RB by in vitro culturing. Next generation RNAseq was employed to analyze these cell lines. Forty-two genes were identified to have acquired mutations after the resistance development, of which thirty-four were found to have mutations in published sequencing studies using prostate cancer samples from patients. Fourteen novel and 2 previously known fusion genes were inferred from the RNA-seq data, and 13 of these were validated by RT-PCR and/or re-sequencing. Four in-frame fusion transcripts could be transcribed into fusion proteins in stably transfected HEK293 cells, including MYH9-EIF3D and LDLR-RPL31P11, which were specific identified or up-regulated in the docetaxel resistant DU145 cells. A panel of 615 gene transcripts was identified to have significantly changed expression profile in the docetaxel resistant cells. These transcriptional changes have potential for further study as predictive biomarkers and as targets of docetaxel treatment.

  • 16. Matsson, Hans
    et al.
    Huss, Mikael
    Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics. Stockholm University, Science for Life Laboratory (SciLifeLab).
    Persson, Helena
    Einarsdottir, Elisabet
    Tiraboschi, Ettore
    Nopola-Hemmi, Jaana
    Schumacher, Johannes
    Neuhoff, Nina
    Warnke, Andreas
    Lyytinen, Heikki
    Schulte-Korne, Gert
    Nothen, Markus M.
    Leppanen, Paavo H. T.
    Peyrard-Janvid, Myriam
    Kere, Juha
    Polymorphisms in DCDC2 and S100B associate with developmental dyslexia2015In: Journal of Human Genetics, ISSN 1434-5161, E-ISSN 1435-232X, Vol. 60, no 7, p. 399-401Article in journal (Refereed)
    Abstract [en]

    Genetic studies of complex traits have become increasingly successful as progress is made in next-generation sequencing. We aimed at discovering single nucleotide variation present in known and new candidate genes for developmental dyslexia: CYP19A1, DCDC2, DIP2A, DYX1C1, GCFC2 (also known as C2orf3), KIAA0319, MRPL19, PCNT, PRMT2, ROBO1 and S100B. We used next-generation sequencing to identify single-nucleotide polymorphisms in the exons of these 11 genes in pools of 100 DNA samples of Finnish individuals with developmental dyslexia. Subsequent individual genotyping of those 100 individuals, and additional cases and controls from the Finnish and German populations, validated 92 out of 111 different single-nucleotide variants. A nonsynonymous polymorphism in DCDC2 (corrected P = 0.002) and a noncoding variant in S100B (corrected P = 0.016) showed a significant association with spelling performance in families of German origin. No significant association was found for the variants neither in the Finnish case-control sample set nor in the Finnish family sample set. Our findings further strengthen the role of DCDC2 and implicate S100B, in the biology of reading and spelling.

  • 17. Sobol, Maria
    et al.
    Klar, Joakim
    Laan, Loora
    Shahsavani, Mansoureh
    Schuster, Jens
    Annerén, Göran
    Konzer, Anne
    Mi, Jia
    Bergquist, Jonas
    Nordlund, Jessica
    Hoeber, Jan
    Huss, Mikael
    Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics. Stockholm University, Science for Life Laboratory (SciLifeLab).
    Falk, Anna
    Dahl, Niklas
    Transcriptome and Proteome Profiling of Neural Induced Pluripotent Stem Cells from Individuals with Down Syndrome Disclose Dynamic Dysregulations of Key Pathways and Cellular Functions2019In: Molecular Neurobiology, ISSN 0893-7648, E-ISSN 1559-1182, Vol. 56, no 10, p. 7113-7127Article in journal (Refereed)
    Abstract [en]

    Down syndrome (DS) or trisomy 21 (T21) is a leading genetic cause of intellectual disability. To gain insights into dynamics of molecular perturbations during neurogenesis in DS, we established a model using induced pluripotent stem cells (iPSC) with transcriptome profiles comparable to that of normal fetal brain development. When applied on iPSCs with T21, transcriptome and proteome signatures at two stages of differentiation revealed strong temporal dynamics of dysregulated genes, proteins and pathways belonging to 11 major functional clusters. DNA replication, synaptic maturation and neuroactive clusters were disturbed at the early differentiation time point accompanied by a skewed transition from the neural progenitor cell stage and reduced cellular growth. With differentiation, growth factor and extracellular matrix, oxidative phosphorylation and glycolysis emerged as major perturbed clusters. Furthermore, we identified a marked dysregulation of a set of genes encoded by chromosome 21 including an early upregulation of the hub gene APP, supporting its role for disturbed neurogenesis, and the transcription factors OLIG1, OLIG2 and RUNX1, consistent with deficient myelination and neuronal differentiation. Taken together, our findings highlight novel sequential and differentiation-dependent dynamics of disturbed functions, pathways and elements in T21 neurogenesis, providing further insights into developmental abnormalities of the DS brain.

  • 18. Song, Lingyun
    et al.
    Zhang, Zhancheng
    Grasfeder, Linda L.
    Boyle, Alan P.
    Giresi, Paul G.
    Lee, Bum-Kyu
    Sheffield, Nathan C.
    Graef, Stefan
    Huss, Mikael
    Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics.
    Keefe, Damian
    Liu, Zheng
    London, Darin
    McDaniell, Ryan M.
    Shibata, Yoichiro
    Showers, Kimberly A.
    Simon, Jeremy M.
    Vales, Teresa
    Wang, Tianyuan
    Winter, Deborah
    Zhang, Zhuzhu
    Clarke, Neil D.
    Birney, Ewan
    Iyer, Vishwanath R.
    Crawford, Gregory E.
    Lieb, Jason D.
    Furey, Terrence S.
    Open chromatin defined by DNaseI and FAIRE identifies regulatory elements that shape cell-type identity2011In: Genome Research, ISSN 1088-9051, E-ISSN 1549-5469, Vol. 21, no 10, p. 1757-1767Article in journal (Refereed)
    Abstract [en]

    The human body contains thousands of unique cell types, each with specialized functions. Cell identity is governed in large part by gene transcription programs, which are determined by regulatory elements encoded in DNA. To identify regulatory elements active in seven cell lines representative of diverse human cell types, we used DNase-seq and FAIRE-seq (Formaldehyde Assisted Isolation of Regulatory Elements) to map open chromatin.'' Over 870,000 DNaseI or FAIRE sites, which correspond tightly to nucleosome-depleted regions, were identified across the seven cell lines, covering nearly 9% of the genome. The combination of DNaseI and FAIRE is more effective than either assay alone in identifying likely regulatory elements, as judged by coincidence with transcription factor binding locations determined in the same cells. Open chromatin common to all seven cell types tended to be at or near transcription start sites and to be coincident with CTCF binding sites, while open chromatin sites found in only one cell type were typically located away from transcription start sites and contained DNA motifs recognized by regulators of cell-type identity. We show that open chromatin regions bound by CTCF are potent insulators. We identified clusters of open regulatory elements (COREs) that were physically near each other and whose appearance was coordinated among one or more cell types. Gene expression and RNA Pol II binding data support the hypothesis that COREs control gene activity required for the maintenance of cell-type identity. This publicly available atlas of regulatory elements may prove valuable in identifying noncoding DNA sequence variants that are causally linked to human disease.

  • 19. Ståhl, Patrik L.
    et al.
    Salmen, Fredrik
    Vickovic, Sanja
    Lundmark, Anna
    Navarro, Jose Fernandez
    Magnusson, Jens
    Giacomello, Stefania
    Asp, Michaela
    Orzechowski Westholm, Jakub
    Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics. Stockholm University, Science for Life Laboratory (SciLifeLab).
    Huss, Mikael
    Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics. Stockholm University, Science for Life Laboratory (SciLifeLab).
    Mollbrink, Annelie
    Linnarsson, Sten
    Codeluppi, Simone
    Borg, Åke
    Ponten, Fredrik
    Costea, Paul Igor
    Sahlen, Pelin
    Mulder, Jan
    Bergmann, Olaf
    Lundeberg, Joakim
    Frisen, Jonas
    Visualization and analysis of gene expression in tissue sections by spatial transcriptomics2016In: Science, ISSN 0036-8075, E-ISSN 1095-9203, Vol. 353, no 6294, p. 78-82Article in journal (Refereed)
    Abstract [en]

    Analysis of the pattern of proteins or messenger RNAs (mRNAs) in histological tissue sections is a cornerstone in biomedical research and diagnostics. This typically involves the visualization of a few proteins or expressed genes at a time. We have devised a strategy, which we call spatial transcriptomics, that allows visualization and quantitative analysis of the transcriptome with spatial resolution in individual tissue sections. By positioning histological sections on arrayed reverse transcription primers with unique positional barcodes, we demonstrate high-quality RNA-sequencing data with maintained two-dimensional positional information from the mouse brain and human breast cancer. Spatial transcriptomics provides quantitative gene expression data and visualization of the distribution of mRNAs within tissue sections and enables novel types of bioinformatics analyses, valuable in research and diagnostics.

  • 20. Troell, Karin
    et al.
    Hallström, Björn
    Divne, Anna-Maria
    Alsmark, Cecilia
    Arrighi, Romanico
    Huss, Mikael
    Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics. Stockholm University, Science for Life Laboratory (SciLifeLab).
    Beser, Jessica
    Bertilsson, Stefan
    Cryptosporidium as a testbed for single cell genome characterization of unicellular eukaryotes2016In: BMC Genomics, ISSN 1471-2164, E-ISSN 1471-2164, Vol. 17, article id 471Article in journal (Refereed)
    Abstract [en]

    Background: Infectious disease involving multiple genetically distinct populations of pathogens is frequently concurrent, but difficult to detect or describe with current routine methodology. Cryptosporidium sp. is a widespread gastrointestinal protozoan of global significance in both animals and humans. It cannot be easily maintained in culture and infections of multiple strains have been reported. To explore the potential use of single cell genomics methodology for revealing genome-level variation in clinical samples from Cryptosporidium-infected hosts, we sorted individual oocysts for subsequent genome amplification and full-genome sequencing. Results: Cells were identified with fluorescent antibodies with an 80 % success rate for the entire single cell genomics workflow, demonstrating that the methodology can be applied directly to purified fecal samples. Ten amplified genomes from sorted single cells were selected for genome sequencing and compared both to the original population and a reference genome in order to evaluate the accuracy and performance of the method. Single cell genome coverage was on average 81 % even with a moderate sequencing effort and by combining the 10 single cell genomes, the full genome was accounted for. By a comparison to the original sample, biological variation could be distinguished and separated from noise introduced in the amplification. Conclusions: As a proof of principle, we have demonstrated the power of applying single cell genomics to dissect infectious disease caused by closely related parasite species or subtypes. The workflow can easily be expanded and adapted to target other protozoans, and potential applications include mapping genome-encoded traits, virulence, pathogenicity, host specificity and resistance at the level of cells as truly meaningful biological units.

  • 21. Zhao, Jing
    et al.
    Lee, Sang Hoon
    Huss, Mikael
    Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics. Stockholm University, Science for Life Laboratory (SciLifeLab).
    Holme, Petter
    The Network Organization of Cancer-associated Protein Complexes in Human Tissues2013In: Scientific Reports, ISSN 2045-2322, E-ISSN 2045-2322, Vol. 3, article id 1583Article in journal (Refereed)
    Abstract [en]

    Differential gene expression profiles for detecting disease genes have been studied intensively in systems biology. However, it is known that various biological functions achieved by proteins follow from the ability of the protein to form complexes by physically binding to each other. In other words, the functional units are often protein complexes rather than individual proteins. Thus, we seek to replace the perspective of disease-related genes by disease-related complexes, exemplifying with data on 39 human solid tissue cancers and their original normal tissues. To obtain the differential abundance levels of protein complexes, we apply an optimization algorithm to genome-wide differential expression data. From the differential abundance of complexes, we extract tissue- and cancer-selective complexes, and investigate their relevance to cancer. The method is supported by a clustering tendency of bipartite cancer-complex relationships, as well as a more concrete and realistic approach to disease-related proteomics.

  • 22. Zhu, Yafeng
    et al.
    Orre, Lukas M.
    Johansson, Henrik J.
    Huss, Mikael
    Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics. Stockholm University, Science for Life Laboratory (SciLifeLab).
    Boekel, Jorrit
    Vesterlund, Mattias
    Fernandez-Woodbridge, Alejandro
    Branca, Rui M. M.
    Lehtiö, Janne
    Discovery of coding regions in the human genome by integrated proteogenomics analysis workflow2018In: Nature Communications, ISSN 2041-1723, E-ISSN 2041-1723, Vol. 9, article id 903Article in journal (Refereed)
    Abstract [en]

    Proteogenomics enable the discovery of novel peptides (from unannotated genomic protein-coding loci) and single amino acid variant peptides (derived from single-nucleotide polymorphisms and mutations). Increasing the reliability of these identifications is crucial to ensure their usefulness for genome annotation and potential application as neoantigens in cancer immunotherapy. We here present integrated proteogenomics analysis workflow (IPAW), which combines peptide discovery, curation, and validation. IPAW includes the SpectrumAI tool for automated inspection of MS/MS spectra, eliminating false identifications of single-residue substitution peptides. We employ IPAW to analyze two proteomics data sets acquired from A431 cells and five normal human tissues using extended (pH range, 3-10) high-resolution isoelectric focusing (HiRIEF) pre-fractionation and TMT-based peptide quantitation. The IPAW results provide evidence for the translation of pseudogenes, lncRNAs, short ORFs, alternative ORFs, N-terminal extensions, and intronic sequences. Moreover, our quantitative analysis indicates that protein production from certain pseudogenes and lncRNAs is tissue specific.

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