Periodic Reporting for period 3 - BIGGER (Biophysics in gene regulation - A genome wide approach)
Reporting period: 2024-01-01 to 2025-06-30
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.
To efficiently characterize large genetic libraries it is necessary to label the strains so that phenotypes and genotypes can be accurately matched. In this project, we use genetic barcodes and analyze the bacteria in compartmentalized microfluidic chambers to keep the clones separate. So far in the project, we have used two proof-of-concept libraries to show conceptually that genotyping from barcodes expressed from the chromosome is possible, and we can successfully link the genotype to the phenotype of the different strains in these libraries.
Our initial idea of following two chromosomal loci in each cell by multicolor labeling fell short since tracking the red fluorophore proved more challenging than we expected. The yellow Venus label, on the other hand, can be accurately located and we have started initial work by measuring the movement of the Venus-labeled loci alone. We are now employing the DuMPLING method to hunt down a good red chromosome marker.
We have developed deep-learning methods to specifically determine the 3D localization of chromosomal loci based on astigmatism. The AI tools beat conventional maximum likelihood-based methods for 3D localization in every aspect. The three loci we have characterized so far display interesting and unexpected 3D localization. These data points will be used as a foundation for more detailed loci mapping.
For the cell cycle regulation project, we have shown that we can use an optical tweezer to isolate one clone from the microfluidic chip for subsequent studies, e.g. whole genome sequencing. In this case, we use green fluorescent cells as proof of principle, and these cells can be accurately identified, tweezed, and isolated from excess red cells.
While developing the Tweeseq method to evaluate the CRISPRi library, we have continued to systematically investigate the regulatory mechanisms behind DNA replication and cell division coordination. Although substantial, this work has created more questions than it has answered. The results are available on BioRxiv (bioRxiv 2021.10.11.463968) and published in PNAS, Knöppel et al. 2023.
Our initial idea of following two chromosomal loci in each cell by multicolor labeling fell short since tracking the red fluorophore proved more challenging than we expected. The yellow Venus label, on the other hand, can be accurately located and we have started initial work by measuring the movement of the Venus-labeled loci alone. We are now employing the DuMPLING method to hunt down a good red chromosome marker.
We have developed deep-learning methods to specifically determine the 3D localization of chromosomal loci based on astigmatism. The AI tools beat conventional maximum likelihood-based methods for 3D localization in every aspect. The three loci we have characterized so far display interesting and unexpected 3D localization. These data points will be used as a foundation for more detailed loci mapping.
For the cell cycle regulation project, we have shown that we can use an optical tweezer to isolate one clone from the microfluidic chip for subsequent studies, e.g. whole genome sequencing. In this case, we use green fluorescent cells as proof of principle, and these cells can be accurately identified, tweezed, and isolated from excess red cells.
While developing the Tweeseq method to evaluate the CRISPRi library, we have continued to systematically investigate the regulatory mechanisms behind DNA replication and cell division coordination. Although substantial, this work has created more questions than it has answered. The results are available on BioRxiv (bioRxiv 2021.10.11.463968) and published in PNAS, Knöppel et al. 2023.
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.
We will continue to look for the missing regulatory molecule to make the initiation-of-replication model complete. Hopefully, we can present a model by the end of the project that can better explain the experimental observations.
We will continue to look for the missing regulatory molecule to make the initiation-of-replication model complete. Hopefully, we can present a model by the end of the project that can better explain the experimental observations.