News

On March 5th we have another talk in the new series on “Heterogeneity in Biological Systems” in the framework of our IRI-Colloquium: Roi Avraham from the Weizmann Institute of Science (http://www.weizmann.ac.il/Biological_Regulation/avraham/avraham-lab-homepage) will give a talk on “Predicting human infection outcome using single cell RNA-seq of blood immune cells“. 

Date: March 5th

Time: 4 p.m.

Venue: IRI Life Sciences
Humboldt-Universität zu Berlin
Philippstr. 13
Michaelis Building (No 18)
Maud Menten Hall (3rd Floor)

https://goo.gl/maps/9LUWXKXj6pv

Abstract:

Management of many bacterial infections is becoming increasingly difficult due to new and rapidly evolving pathogens with increased virulence and drug resistance. Promising alternative approaches to targeting pathogens are to harness the host’s own response to infection or to target virulent processes of the pathogen. To realize these intriguing alternatives, a comprehensive and systematic understanding of the complex dynamics between host and pathogen is required. Using a powerful combination of cutting-edge single cell genetic and genomic approaches, we wish to address what forms the basis for successful immune clearance, from the level of individual infected cells to that of the whole organism, and why, in some cases, sterilization is incomplete?

In this talk, I will demonstrate our approach that applies single cell analysis of models of infection of cultured blood immune cells with different pathogens and of human patient samples. We elucidate the complexity of the human immune system in health and disease, to understand what are the important determinant for successful control of infection. This approach allowed us to identify cell-type specific activation biomarkers that can predict risk to infectious diseases, and also provide indications to changes in immune correlates at very easy stages of infection.

On February 6th we have another guest speaker. Steven Altschuler from the University of California (http://www.altschulerwulab.org/home)  will give a talk on Cellular decisions in rapidly dividing tissues. 

Date: February 6th
Time: 4 p.m.
Venue: IRI Life Sciences,
Humboldt-Universität zu Berlin,
Philippstr. 13, Michaelis Building (No 18),
Maud Menten Hall (3rd Floor)
https://goo.gl/maps/9LUWXKXj6pv

Cellular decisions in rapidly dividing tissues

We will talk about recent progress in understanding how cells make decisions in rapidly dividing populations. In the first part, we will report on single-cell cancer fate decisions after non-lethal dose of chemotherapy. Chemotherapy is designed to induce cell death. However, at non-lethal doses, cancer cells can choose to remain proliferative or become senescent. The slow development of senescence makes studying this decision challenging. In the second part, we will report on how network crosstalk in the intestinal epithelium regulates cell lineage decisions. We will make use of a novel 2-D gut organoid culture system to dissect how small intestinal epithelium translates combinatorial signals into changes in cell-type composition. Our study helps links the size of the proliferating progenitor compartment with cell-fate specification, enabling a unified and diverse response to the microenvironment.

On January 15th we have a guest speaker. Olivier Pertz from the University of Bern will talk about his work on Decoding and Re-encoding MAPK Fate Decision Signaling.

Date: January 15th
Time: 4 p.m.
Venue: IRI Life Sciences,
Humboldt-Universität zu Berlin,
Philippstr. 13, Michaelis Building (No 18),
Maud Menten Hall (3rd Floor)
https://goo.gl/maps/9LUWXKXj6pv

Decoding and Re-encoding MAPK Fate Decision Signaling

Olivier Pertz, Institute of Cell Biology, University of Bern
Cells dynamically sense and respond to ever changing external stimuli through sophisticated signaling networks. Accordingly, signaling dynamics rather than steady states control fate decisions. For many signaling pathways, heterogeneous dynamic signaling states occur within distinct cells, explaining fate variability observed within a cell population. Measuring single cell signaling dynamics is therefore key to understand how cellular responses correlate with specific cell fate decisions. Here, we combine biosensor imaging, microfluidics, optogenetics and mathematical modelling to map how different MAPK signalling network circuitries fine tune ERK activity dynamics at the single cell level.
In PC-12 cells, a classic model for fate determination, we observe that different growth factors (GFs) wire the MAPK pathway differently to modify the population distribution of
transient/sustained ERK states that are known to induce proliferation/differentiation fates.
EGF only induces transient ERK states; NGF results in a mix of transient/sustained ERK states, with a sharp increase of the latter at high GF input; FGF gradually modifies the population distribution of transient/sustained ERK states in response to augmenting GF input. The latter feature might be consistent with FGF-dependent fate determination in developmental morphogen gradients. Thus, the distinctive GFs wire the MAPK network differently to control the population distributions of transient/sustained ERK states, and fates. Temporal perturbations applied using microfluidics and optogenetics provide highly informative novel signalling states that allow us to infer the feedback structure inherent to the different networks. Ultimately, this allows us to reprogram fate decisions at will by evoking synthetic dynamic signalling states using temporal perturbations.
I will also discuss on another fate determination system in which MCF10A breast epithelial
cells constantly senses the state of the cell collective, and reacts by spatially tuning  survival and proliferation fates to ensuring a critical cell density necessary for proper barrier function. Here we observe two single-cell ERK signalling modes that consist either of stochastic pulses (in presence of GFs), or of co-ordinated ERK waves across multiple cell layers that originate around apoptotic extruding cells (in absence of GFs or in presence of cytotoxic agents). We show that such ERK activity pulses provide a survival signal for about 3 hours allowing to constantly fine tune fate determination during this epithelial homeostasis process. A further degree of spatio-temporal signalling complexity is observed when these cells are grown as 3D epithelial spheroids which can then explain morphogenetic processes such as lumen formation.
Together, these results showcase the rich variety of information processing/transfer enabled by the MAPK/ERK pathway to warrant robust regulation fate decisions at biologically relevant time/length scales.

On December 19th we have a guest speaker: Donate Weghorn from the Centre of Genomic Regulation, Barcelona will talk about Probabilistic approaches to inference of mutation rate and selection in cancer.

Date: Thursday, December 19th

Time: 4 p.m.

Venue: IRI Life Sciences, Humboldt-Universität zu Berlin,

Philippstr. 13, Michaelis Building (No 18),

Maud Menten Hall (3rd Floor)

https://goo.gl/maps/9LUWXKXj6pv

Probabilistic approaches to inference of mutation rate and selection in cancer

Cancer is a highly complex system that evolves asexually under high mutation rates and strong selective pressures. Cancer genomics efforts have identified genes and regulatory elements driving cancer development and neoplastic progression. The detection of both significantly mutated (positive selection) and undermutated (negative selection) genes is completely confounded by the genomic heterogeneity of the cancer mutation rate. Here, I present an approach to address mutation rate heterogeneity in order to increase the power and accuracy of selection inference. Using a hierarchical model, we infer the distribution of mutation rates across genes that underlies the observed distribution of the synonymous mutation count within a given cancer type. This enables the inference of the probability of nonsynonymous mutations without additional parameters, however explicitly taking into account cancer-type-specific mutational signatures, which are known to be highly distinct. We then augmented our test through integrating information at the single-nucleotide level. Based on a model that accounts for the extended sequence context (> 5-mers) around mutated sites, this second component of the test identifies genes with an excess of mutations in specific nucleotide contexts, which deviate from the characteristic context around neutrally evolving passenger mutations. Using the combined test, we discovered a catalogue of well-known cancer driver genes as well as a long tail of novel candidate cancer genes with mutation frequencies as low as 1% and functional supporting evidence.

We are organizing an upcoming workshop on the highly relevant topic of Deep Learning (DL). Established DL domain experts Dagmar Kainmüller, Jonathan Ronen and Grégroire Montavon will cover the specialized domains of image-classification, deep learning for genomic data integration with applications in cancer diagnosis and interpretation of DL results.

The workshop takes place on January 16th/17th, 2019. More information are available at

https://www.comp-cancer.de/dl_workshop/

Places are limited to 20 and CompCancer graduate school members have prioritized access, however, vacant seats will be given to external participants.