Periodic Reporting for period 4 - BIGGER (Biophysics in gene regulation - A genome wide approach)
Okres sprawozdawczy: 2025-07-01 do 2025-12-31
In the flurry of chemical reactions happening simultaneously inside a bacterium, growth and division must be precisely coordinated, or the race is over in the highly competitive environment. The number of initiated DNA replication processes and the number of cell divisions have to be equal, or the cell loses genetic material or accumulates DNA with equally devastating consequences.
Here, we can draw parallels to multicellular organisms such as ourselves. When synchronization of DNA replication and cell division malfunctions in a single-cell organism, lethality is essentially inevitable. If some of our human cells fail to coordinate these processes, it usually leads to elimination, but sometimes to uncontrolled growth and eventually cancer.
We can conclude that whatever process controls cell division and DNA replication must be precise and one would thus expect that E. coli bacteria living under similar conditions would behave very similarly. However, this is not the case. Cell size and lifespan vary greatly between genetically identical bacteria, even if the external conditions are constant. To investigate this variation and potentially pinpoint the regulatory mechanism, we will create a CRISPRi library of cells with different gene perturbations and study what perturbations impact cell cycle control. We have previously shown that the E. coli bacterium starts copying its DNA when it reaches a certain volume and how long it then takes before the cell divides depends on how fast each individual grows. However, despite decades of efforts from us and others, it is still not clear how the cell decides it is big enough.
If cell cycle regulation is an example of a scientific problem that has received ample attention lately, the bacterial chromosome structure represents the opposite case. It is not clear if the 3D structure is at all important for gene regulation and DNA maintenance, but if this is the case, events like gene transfer and other sequence rearrangements have to be dealt with. By labeling different chromosomal loci in a large cell library and following these loci through the cell cycle, we will create a structural framework that we can use to model a high-resolution 4D chromosome map.
Here, we can draw parallels to multicellular organisms such as ourselves. When synchronization of DNA replication and cell division malfunctions in a single-cell organism, lethality is essentially inevitable. If some of our human cells fail to coordinate these processes, it usually leads to elimination, but sometimes to uncontrolled growth and eventually cancer.
We can conclude that whatever process controls cell division and DNA replication must be precise and one would thus expect that E. coli bacteria living under similar conditions would behave very similarly. However, this is not the case. Cell size and lifespan vary greatly between genetically identical bacteria, even if the external conditions are constant. To investigate this variation and potentially pinpoint the regulatory mechanism, we will create a CRISPRi library of cells with different gene perturbations and study what perturbations impact cell cycle control. We have previously shown that the E. coli bacterium starts copying its DNA when it reaches a certain volume and how long it then takes before the cell divides depends on how fast each individual grows. However, despite decades of efforts from us and others, it is still not clear how the cell decides it is big enough.
If cell cycle regulation is an example of a scientific problem that has received ample attention lately, the bacterial chromosome structure represents the opposite case. It is not clear if the 3D structure is at all important for gene regulation and DNA maintenance, but if this is the case, events like gene transfer and other sequence rearrangements have to be dealt with. By labeling different chromosomal loci in a large cell library and following these loci through the cell cycle, we will create a structural framework that we can use to model a high-resolution 4D chromosome map.
In this project, we set out to understand how the chromosome moves, folds, and interacts with the cell’s replication machinery over time. To this end, we developed a suite of new experimental and computational tools that allowed us to watch the chromosome in action inside living cells.
One major advance was the ability to read out the identity of individual cells directly on a microfluidic chip using chromosome‑encoded barcodes. This “in situ genotyping” approach allowed us to perform optical pooled screens in bacteria, where we can measure spatial phenotypes in thousands of cells and still know exactly which genetic variant each one carries. Using this platform, we analyzed libraries of strains with fluorescently labeled chromosome positions and mapped how different loci behave inside the cell.
To track how pairs of chromosome sites move relative to each other, we developed a robust two‑color labeling system. After extensive optimization, we identified a combination of fluorescent tags that provides stable, high‑precision tracking of two loci at once. Using deep‑learning–based 3D localization, we can now pinpoint chromosome positions with better than 60‑nanometer accuracy throughout the cell cycle.
These tools revealed new principles of chromosome behavior. We found that gene loci move in a restricted, “subdiffusive” manner but still explore the full width of the cell within about a minute. We also discovered that the replication machinery, the replisomes, remain confined to a small region of the cell, and that chromosome sites move toward them rather than the replisomes traveling along the DNA. This supports a model in which the DNA is actively brought to the replication machinery, not the other way around.
To complement these dynamic measurements, we developed a time‑resolved version of Hi‑C, a method that captures physical contacts between different parts of the chromosome. By profiling around 100,000 cells per experiment and sorting them into 25 cell‑cycle stages, we obtained a detailed view of how short‑range chromosome interactions change as the cell grows and divides.
Finally, we explored how chromosome dynamics are coordinated with the cell cycle. By tracking replication machinery across thousands of generations in different mutant strains, we showed that the timing of DNA replication initiation depends more on the balance between ATP‑ and ADP‑bound forms of the initiator protein DnaA than on its absolute concentration. We also discovered that two regulatory systems, DARS and datA, act redundantly to stabilize this process. Using a new method we call Tweez‑seq, which isolates individual cells directly from the microfluidic chip, we identified additional genes, both known and previously uncharacterized, that influence the coupling between DNA replication and cell division.
One major advance was the ability to read out the identity of individual cells directly on a microfluidic chip using chromosome‑encoded barcodes. This “in situ genotyping” approach allowed us to perform optical pooled screens in bacteria, where we can measure spatial phenotypes in thousands of cells and still know exactly which genetic variant each one carries. Using this platform, we analyzed libraries of strains with fluorescently labeled chromosome positions and mapped how different loci behave inside the cell.
To track how pairs of chromosome sites move relative to each other, we developed a robust two‑color labeling system. After extensive optimization, we identified a combination of fluorescent tags that provides stable, high‑precision tracking of two loci at once. Using deep‑learning–based 3D localization, we can now pinpoint chromosome positions with better than 60‑nanometer accuracy throughout the cell cycle.
These tools revealed new principles of chromosome behavior. We found that gene loci move in a restricted, “subdiffusive” manner but still explore the full width of the cell within about a minute. We also discovered that the replication machinery, the replisomes, remain confined to a small region of the cell, and that chromosome sites move toward them rather than the replisomes traveling along the DNA. This supports a model in which the DNA is actively brought to the replication machinery, not the other way around.
To complement these dynamic measurements, we developed a time‑resolved version of Hi‑C, a method that captures physical contacts between different parts of the chromosome. By profiling around 100,000 cells per experiment and sorting them into 25 cell‑cycle stages, we obtained a detailed view of how short‑range chromosome interactions change as the cell grows and divides.
Finally, we explored how chromosome dynamics are coordinated with the cell cycle. By tracking replication machinery across thousands of generations in different mutant strains, we showed that the timing of DNA replication initiation depends more on the balance between ATP‑ and ADP‑bound forms of the initiator protein DnaA than on its absolute concentration. We also discovered that two regulatory systems, DARS and datA, act redundantly to stabilize this process. Using a new method we call Tweez‑seq, which isolates individual cells directly from the microfluidic chip, we identified additional genes, both known and previously uncharacterized, that influence the coupling between DNA replication and cell division.
Our 3D-resolved single-molecule tracking at sub-ms time scale is beyond state-of-the-art. However, our method to determine barcodes expressed from the bacterial chromosome might have a bigger scientific impact since this approach has many practical applications. The Tweez-seq method represents an important step forward as it allows dynamic characterization of mutants in non-barcoded libraries.