Last talk of the #CSSingleCells23 conference:
Karin Pelka, Gladstone/UCSF
https://pelkalab.org/

Spatially organized #immune hubs in #colon #cancer
#ColonCancer
#scRNAseq

https://pubmed.ncbi.nlm.nih.gov/34450029/

Then: predict cellular interaction networks via correlations of gene program activities across #tumors

anti-tumor hubs in tumors, ISGs including CXCR3 ligands, differs between tumor types (MMR+ or -)

have data from clinical trial (biopsies before and after treatment)
https://pubmed.ncbi.nlm.nih.gov/36702949/

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Last session of the conference! Continuing theme of "Cell identity in situ"

Parker Côté, DFCI
in Li Lab
https://ki.mit.edu/people/clinical-investigators-research-fellows/hojun-li

The #transcriptional dynamics of human #hematopoiesis at #SingleCell resolution

do #StemCells and #ProgenitorCells in #hematopoietic system (#HSPC) change with age?

HSPCs exist on a continuum of cell types

They identified #GeneExpression programs active in uncommitted cells, looking across human development (fetal to aged)

https://www.biorxiv.org/content/10.1101/2021.08.25.457678v1

#CSSingleCells23

Now Siddharth Dey, UCSB
https://deylab.com/

Photo-sensitive barcodes combined with topologically imposed light gradients enable spatially-resolved #SingleCell #transcriptomics and #epigenomics

a new technology: scSTAMP-seq which enables use of light patterning to achieve dynamic spatial resolution

adaptation of STAMP-seq

also applying to DNA methylation
https://www.biorxiv.org/content/10.1101/2023.05.06.539708v1

#CSSingleCells23

Next is Melanie Samuel from BCM
https://thesamuellab.org/

Molecular regulation of #immune cell #plasticity and function in the #brain

"Our brain is the ultimate time machine" 🙂

How to target #synapses (for intervention) while preserving them (to avoid "turning back the clock"

Possibility that #microglia could be harnessed

partnered with IMPC (impc.org) to find microglia regulators in retina
one cool hit: SIRPα
it's NOT involved in #phagocytosis... surprise

#CSSingleCells23

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First speaker of the session (Cell identity in situ)
is Elana Fertig
of Convergence Institute at Johns Hopkins
https://fertiglab.com/

She has background in weather prediction (!) ⛈️ which has convergence with predictive medicine (such as huge data sets)

Looks at #PancreaticCancer with spatial #proteomics
now #scRNAseq

Developed CoGAPS matrix factorization, can identify cell state transitions

Using PhysiCell to build models
http://physicell.org/

#cancer
#SingleCell
#CSSingleCells23

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Final session of the great conference is

Cell identity in situ

#CSSingleCells23

Judith Zaugg from EMBL
https://www.embl.org/groups/zaugg/

How do cells integrate extrinsic signals and intrinsic state? A systems #epigenetics approach

Individual uniqueness (of people) -- molecular basis of #variation
Needed: systems epigenetics framework
signaling -- TFs -- regulatory elements -- genes

tools for inference & evaluation of enhancer-mediated gene regulatory networks called GRaNIE and GRaNPA 😃
https://www.embopress.org/doi/full/10.15252/msb.202311627

example of problem: https://www.embopress.org/doi/full/10.15252/msb.20209539

#CSSingleCells23

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Second half of the "variation and information" session #CSSingleCells23
led off by Sam Morris of WashU
http://morrislab.wustl.edu/

Multi-omic lineage tracing: insights into reprogramming cell identity

her piece in *Development*, "The evolving concept of cell identity in the single cell era"

working on "induced hepatocytes", start with fibroblasts, via "induced endoderm progenitors"

new work on #adipocytes
https://www.biorxiv.org/content/10.1101/2023.06.01.543318v1

#reprogramming
#StemCells
#CellIdentity
#CellFate

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Yogesh Goyal at Northwestern Feinberg
https://www.goyallab.org/

Topic:
Tracing rare cell plasticity and diverse fate decisions in single cancer cells

Begins with reference to (and pic of) Monod's *Chance and Necessity*
#CellFate
#SingleCell
#CSSingleCells23

Emphasizing non-genetic differences between cells, something we can only see at single-cell resolution

Refers to Luria & Delbruck 1943 about bacterial resistance (to phage), relevant to cancer resistance to therapy (selected)

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Now Katie Pollard from UCSF
https://docpollard.org/

Resolving single-cell regulatory elements across species and contexts with CellWalker2

lab builds #statistical models and #ComputationalBiology tools
#neuroscience

did microdissection then single-cell ATAC-seq
developed CellWalker to solve challenges in resolving regulatory elements
https://genomebiology.biomedcentral.com/articles/10.1186/s13059-021-02279-1

#GeneExpression
#genomics
#SingleCell
#CSSingleCells23

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First speaker: Jingyi Jessica Li, UCLA
http://jsb.ucla.edu/

Enhancing #statistical rigor in single-cell data analysis using synthetic negative controls

"In #genomics, the negative control is often not so obvious"

How to choose null hypothesis? question is often "too abstract for biologists" 🤓

Now discussing (infamous) problems with dubious use of t-SNE

developed tool called scDEED
https://www.biorxiv.org/content/10.1101/2023.04.21.537839v1

#CSSingleCells23
#ComputationalBiology
#statistics

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First session of the last day at this great conference,
Conceptual power of single cell biology
https://www.cell-symposia.com/conceptual-single-cells-2023/

The session is "Variation and information"
#CSSingleCells23

#BiologicalInformation

Last speaker of the day is the keynote:
Xiaowei Zhuang
Harvard University
https://zhuang.harvard.edu/pi.html

Spatially resolved #SingleCell genomics and cell atlas of the #brain

Explaining MERFISH, now I get it 🤓

Now have adapted to #epigenome: https://pubmed.ncbi.nlm.nih.gov/36272405/

and to thick tissue:
https://www.biorxiv.org/content/10.1101/2023.07.21.550124v1

Now discussing this epic MERFISH atlas of the whole mouse brain
https://www.biorxiv.org/content/10.1101/2023.03.06.531348v1

use imputation to infer cell-cell interactions (several hundred cell types), cool

#CSSingleCells23

Now Neda Bagheri at U of Washington
https://www.bagherilab.com/

Emulating emergent spatio-temporal cell population dynamics with #machinelearning algorithms remains challenging

Population dynamics arise from autonomous #SingleCell decisions
e.g. in context of #cancer progression

Created tool called ARCADE = Agent-based Representation of Cells And Dynamic Environments
https://bagherilab.com/resources.php

But model is computationally expensive...
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#ComputationalBiology
#SystemsBiology
#CSSingleCells23

Rong Fan at Yale
https://www.fan-lab.org/

Spatial Multi-Omics Sequencing at Cellular Level via Deterministic Barcoding in Tissue

first slide called "2006--the ice age of single-cell biology," referring to review article by Johanna Joyce

Recent great technical advance: spatial CITE-seq
https://www.nature.com/articles/s41587-023-01676-0

and spatial ATAC-seq

#Transcriptomics
#Epigenetics
#CSSingleCells23

Aviv Regev (Genentech)
https://www.gene.com/scientists/our-scientists/aviv-regev

From cell to perturbation atlases

Deciphering causal intra- and intercellular circuits

Using Perturb-seq
https://www.biorxiv.org/content/10.1101/2023.01.23.525198v1

#SystemsBiology
#CSSingleCells23
#GeneExpression

Now want to do multiple perturbations in one cell... do effects combine? Can do this with orig Perturb-seq, then categorize interactions

But the space of interactions is far bigger than the number of cells (in universe)

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first speaker of this session:
Leeat Keren, Weizmann Institute of Science
Escalating high-dimensional imaging using combinatorial multiplexing and #deeplearning

Why can't combinatorial staining approaches (used with #RNA) work with proteins?
overlapping signals cause big math problems

And... #proteins about 10,000X more abundant than RNA

idea: use structure of biological images to constrain math solutions after combinatorial staining of proteins

#CSSingleCells23

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Third major session at Conceptual Power of Single-Cell Biology
is "Cells in context"
chaired by Melanie Samuel (BCM) and Karin Pelka (Gladstone/UCSF)

Very cool topics incoming

#CSSingleCells23

Sophie Dumont at UCSF
http://www.dumontlab.ucsf.edu/

#Chromosome size alters #kinetochore attachment stability and alignment order in mammalian #mitosis

Lab interested in #SelfOrganization and emergent mechanics across scales.... "biological structures build themselves" using only local cues they get global information. mitotic spindle a great example

kinetochores attach, sense tension, can make mistakes which are corrected. how does this work when chromosomes vary in size?

#CSSingleCells23

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Polly Fordyce at Stanford
http://www.fordycelab.com/

Question: How do #transcription factors activate transcription?
Outside the DNA binding domain of a TF, there are numerous disordered domains, including activation domains that interact with co-activators--
very little known about that

activation domains are disordered, poorly conserved, and binding to co-activators is very low affinity

developed a #microfluidic platform to measure, tech called STAMMP

#CSSingleCells23

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