Biology subjects

Andersson, A.

Publications and source records attributed to Andersson, A..

29 records · Page 2Linked to original sources

bioRxiv2021

A Landmark-based Common Coordinate Framework for Spatial Transcriptomics Data

1The increasing amount of spatial transcriptomics data prompts for means to amalgamate observations from distinct experiments, especially attractive is to cast quantities from different sources into a common coordinate frame-work (CCF) to relate signals across space. We here present a method that enables transfer of information from multiple samples to a reference representing a CCF, and show its utility by analyzing an assortment of real and synthetic data sets.

bioinformatics↗

bioRxiv2021

The spatial landscape of clonal somatic mutations in benign and malignant tissue

Defining the transition from benign to malignant tissue is fundamental to improve early diagnosis of cancer. Here, we provide an unsupervised approach to study spatial genome integrity in situ to gain molecular insight into clonal relationships. We employed spatially resolved transcriptomics to infer spatial copy number variations in >120 000 regions across multiple organs, in benign and malignant tissues. We demonstrate that genome-wide copy number variation reveals distinct clonal patterns within tumours and in nearby benign tissue. Our results suggest a model for how genomic instability arises in histologically benign tissue that may represent early events in cancer evolution. We highlight the power of an unsupervised approach to capture the molecular and spatial continuums in a tissue context and challenge the rationale for treatment paradigms, including focal therapy.

genomics↗

bioRxiv2021

Adult medial habenula neurons require GDNF receptor GFRalpha1 for synaptic stability and function

The medial habenula (mHb) is an understudied small brain nucleus linking forebrain and midbrain structures controlling anxiety and fear behaviors. The mechanisms that maintain the structural and functional integrity of mHb neurons and their synapses remain unknown. Using spatio-temporally controlled Cre-mediated recombination in adult mice, we found that the GDNF receptor alpha 1 (GFR1) is required in adult mHb neurons for synaptic stability and function. mHb neurons express some of the highest levels of GFR1 in the mouse brain, and acute ablation of GFR1 results in loss of septo-habenular and habenulo-interpeduncular glutamatergic synapses, with the remaining synapses displaying reduced numbers of presynaptic vesicles. Chemo- and opto-genetic studies in mice lacking GFR1 revealed impaired circuit connectivity, reduced AMPA receptor postsynaptic currents, and abnormally low rectification index of AMPARs, suggesting reduced Ca2+-permeability. Further biochemical and proximity ligation assay studies defined the presence of GluA1/GluA2 (Ca2+-impermeable) as well as GluA1/GluA4 (Ca2+-permeable) AMPAR complexes in mHb neurons, as well as clear differences in the levels and association of AMPAR subunits in mHb neurons lacking GFR1. Finally, acute loss of GFR1 in adult mHb neurons reduced anxiety-like behavior and potentiated context-based fear responses, phenocopying the effects of lesions to septal projections to the mHb. These results uncover an unexpected function for GFR1 in the maintenance and function of adult glutamatergic synapses, and reveal a potential new mechanism for regulating synaptic plasticity in the septo-habenulo-interpeduncular pathway and attuning of anxiety and fear behaviors.

neuroscience↗

bioRxiv2021

ISTDECO: In Situ Transcriptomics Decoding by Deconvolution

In Situ Transcriptomics (IST) is a set of image-based transcriptomics approaches that enables localisation of gene expression directly in tissue samples. IST techniques produce multiplexed image series in which fluorescent spots are either present or absent across imaging rounds and colour channels. A spots presence and absence form a type of barcoded pattern that labels a particular type of mRNA. Therefore, the expression of a gene can be determined by localising the fluorescent spots and decode the barcode that they form. Existing IST algorithms usually do this in two separate steps: spot localisation and barcode decoding. Although these algorithms are efficient, they are limited by strictly separating the localisation and decoding steps. This limitation becomes apparent in regions with low signal-to-noise ratio or high spot densities. We argue that an improved gene expression decoding can be obtained by combining these two steps into a single algorithm. This allows for an efficient decoding that is less sensitive to noise and optical crowding. We present IST Decoding by Deconvolution (ISTDECO), a principled decoding approach combining spectral and spatial deconvolution into a single algorithm. We evaluate ISTDECO on simulated data, as well as on two real IST datasets, and compare with state-of-the-art. ISTDECO achieves state-of-the-art performance despite high spot densities and low signal-to-noise ratios. It is easily implemented and runs efficiently using a GPU. ISTDECO implementation, datasets and demos are available online at: github.com/axanderssonuu/istdeco

bioinformatics↗

bioRxiv2021

Spatial Transcriptomics to define transcriptional patterns of zonation and structural components in the liver

Reconstruction of heterogeneity through single-cell transcriptional profiling has greatly advanced our understanding of the spatial liver transcriptome in recent years. However, global transcriptional differences across lobular units remain elusive in physical space. Here, we implement Spatial Transcriptomics to perform transcriptomic analysis across sectioned liver tissue. We confirm that the heterogeneity in this complex tissue is predominantly determined by lobular zonation. By introducing novel computational approaches, we enable transcriptional gradient measurements between tissue structures, including several lobules in a variety of orientations. Further, our data suggests the presence of previously transcriptionally uncharacterized structures within liver tissue, contributing to the overall spatial heterogeneity of the organ. This study demonstrates how comprehensive spatial transcriptomic technologies can be used to delineate extensive spatial gene expression patterns in the liver, indicating its future impact for studies of liver function, development and regeneration as well as its potential in pre-clinical and clinical pathology.

genomics↗

bioRxiv2020

Genome-wide Spatial Expression Profiling in FFPE Tissues

Formalin-fixed paraffin embedding (FFPE) is the most widespread long-term tissue preservation approach. Here we present a procedure to perform genome-wide spatial analysis of mRNA in FFPE tissue sections. The procedure takes advantage of well-established, commercially available methods for imaging and spatial barcoding using slides spotted with barcoded oligo(dT) probes to capture the 3 end of mRNA molecules in tissue sections. First, we conducted expression profiling and cell type mapping in coronal sections from the mouse brain to demonstrate the methods capability to delineate anatomical regions from a molecular perspective. Second, we explored the spatial composition of transcriptomic signatures in ovarian carcinosarcoma samples using data driven analysis methods, exemplifying the methods potential to elucidate molecular mechanisms in heterogeneous clinical samples.

genetics↗

bioRxiv2020

Unsupervised cell interaction profiling reveals major architectural differences between small intestinal and colonic epithelial crypts

Cellular identity in complex multicellular organisms is strictly maintained over the course of life. This control is achieved in part by the organ structure itself, such that neighboring cells influence each others identity. However, large-scale investigation of the cellular interactome has been technically challenging. Here, we develop CIM-seq, an unsupervised and high-throughput method to analyze direct physical cell-cell interactions between every cell type in a given tissue. CIM-seq is based on RNA sequencing of incompletely dissociated cells, followed by computational deconvolution of these into their constituent cell types using machine learning. We use CIM-seq to define the cell interaction landscape of the mouse small intestinal and colonic epithelium, uncovering both known and novel interactions. Specifically, we find that the general architecture of the stem cell niche is radically different between the two tissues. In small intestine, the stem-Paneth cell interaction forms an exceptionally strong and exclusive niche, in which Paneth cells provide Wnt ligands1. In colonic epithelium, no similar compartment exists to support stem cells, and Wnt signaling is provided by a mesenchymal cell layer2,3. However, colonic stem cells are supported by an adjacent, previously unrecognized goblet cell subtype expressing the wound-healing marker Plet1, which is also highly upregulated during regeneration of colon epithelium. These results identify novel cellular interactions specific for the colonic stem cell niche and suggest an additional level of structural control in the colon. CIM-seq is broadly applicable to studies that aim to simultaneously investigate the constituent cell types and the global interaction profile in a specific tissue.

developmental biology↗

bioRxiv2020

Super-resolved spatial transcriptomics by deep data fusion

In situ RNA capturing has made it possible to record histology and spatial gene expression from the same tissue section. Here, we introduce a method that combines data from both modalities to infer super-resolved full-transcriptome expression maps. Our method unravels transcriptional heterogeneity in micrometer-scale anatomical features and enables image-based in silico spatial transcriptomics without hybridization or sequencing.

bioinformatics↗

bioRxiv2019

Spatial mapping of cell types by integration of transcriptomics data

Spatial transcriptomics and single cell RNA-sequencing offer complementary insights into the transcriptional expression landscape. We here present a probabilistic method that integrates data from both techniques, leveraging their respective strengths in such a way that we are able to spatially map cell types to a tissue. The method is applied to several different types of tissue where the spatial cell type topographies are successfully delineated.

bioinformatics↗

bioRxiv2019

Activin receptor ALK4 coordinates extracellular signals and intrinsic transcriptional programs to regulate development of cortical somatostatin interneurons

Although the role of transcription factors in fate specification of cortical interneurons is well established, how these interact with extracellular signals to regulate interneuron development is poorly understood. Here we show that the activin receptor ALK4 is a key regulator of the specification of somatostatin interneurons. Mice lacking ALK4 in GABAergic neurons of the medial ganglionic eminence (MGE) showed marked deficits in distinct subpopulations of somatostatin interneurons from early postnatal stages of cortical development. Specific loses were observed among distinct subtypes of somatostatin+/Reelin+ double-positive cells, including Hpse+ layer IV cells targeting parvalbumin+ interneurons, leading to quantitative alterations in the inhibitory circuitry of this layer. Activin-mediated ALK4 signaling in MGE cells induced interaction of Smad2 with SATB1, a transcription factor critical for somatostatin interneuron development, and promoted SATB1 nuclear translocation and repositioning within the somatostatin gene promoter. These results indicate that intrinsic transcriptional programs interact with extracellular signals present in the environment of MGE cells to regulate cortical interneuron specification.

neuroscience↗

bioRxiv2019

Membrane integration and topology of RIFIN and STEVOR proteins of the Plasmodium falciparum parasite

The malarial parasite Plasmodium, infects red blood cells by remodeling them and transporting its own proteins to their cell surface. These proteins trigger adhesion of infected cells to uninfected cells (rosetting), and to the vascular endothelium, obstructing blood flow and contributing to pathogenesis. RIFINs (P. falciparum-encoded repetitive interspersed families of polypeptides) and STEVORs (subtelomeric variable open reading frame), are two classes of proteins that are involved in rosetting. Here we study the membrane insertion and topology of three RIFIN and two STEVOR proteins, employing a well-established assay that uses N-linked glycosylation of sites within the protein as a measure to assess the topology a protein adopts when inserted into the ER membrane. Our results indicate that all the proteins tested assume an overall topology of Ncyt-Ccyt, with predicted transmembrane helices TM1 and TM3 integrated into the ER membrane. We also show that the segments predicted as TM2 do not reside in the membrane. Our conclusions are consistent with other recent topology studies on RIFIN and STEVOR proteins.

biochemistry↗