Search tips
Search criteria

Results 1-8 (8)

Clipboard (0)

Select a Filter Below

Year of Publication
author:("feno, Michael")
1.  The Three-Dimensional Architecture of a Bacterial Genome 
Molecular cell  2011;44(2):10.1016/j.molcel.2011.09.010.
We have determined the three-dimensional (3D) architecture of the Caulobacter crescentus genome by combining genome-wide chromatin interaction detection, live-cell imaging, and computational modeling. Using chromosome conformation capture carbon copy (5C) technology, we derive ~13 Kb resolution 3D models of the Caulobacter genome. These models illustrate that the genome is ellipsoidal with periodically arranged arms. The parS sites, a pair of short contiguous sequence elements involved in chromosome segregation, are positioned at one pole of this structure, where they nucleate a compact chromatin conformation. Both 5C and imaging experiments demonstrate that placing these sequence elements at new genomic positions yields large-scale rotations of the genome within the cell. Utilizing automated fluorescent imaging, we orient the genome within the cell and illustrate that within the resolution of our data the parS proximal region is the only portion of the genome stably attached to the cell envelope. Our approach provides an experimental paradigm for deriving insight into the cis-determinants of 3D genome architecture.
PMCID: PMC3874842  PMID: 22017872
2.  Assembly of the Caulobacter cell division machine 
Molecular microbiology  2011;80(6):1680-1698.
Cytokinesis in Gram-negative bacteria is mediated by a multiprotein machine (the divisome) that invaginates and remodels the inner membrane, peptidoglycan, and outer membrane. Understanding the order of divisome assembly would inform models of the interactions among its components and their respective functions. We leveraged the ability to isolate synchronous populations of Caulobacter crescentus cells to investigate assembly of the divisome and place the arrival of each component into functional context. Additionally, we investigated the genetic dependency of localization among divisome proteins and the cell cycle regulation of their transcript and protein levels to gain insight into the control mechanisms underlying their assembly. Our results revealed a picture of divisome assembly with unprecedented temporal resolution. Specifically, we observed 1) initial establishment of the division site, 2) recruitment of early FtsZ-binding proteins, 3) arrival of proteins involved in peptidoglycan remodeling, 4) arrival of FtsA, 5) assembly of core divisome components, 6) initiation of envelope invagination, 7) recruitment of polar markers and cytoplasmic compartmentalization, and 8) cell separation. Our analysis revealed differences in divisome assembly among Caulobacter and other bacteria that establish a framework for identifying aspects of bacterial cytokinesis that are widely conserved from those that are more variable.
PMCID: PMC3707389  PMID: 21542856
divisome; FtsZ; septum; Caulobacter; cell division
3.  Automated Quantitative Live Cell Fluorescence Microscopy 
Advances in microscopy automation and image analysis have given biologists the tools to attempt large scale systems-level experiments on biological systems using microscope image readout. Fluorescence microscopy has become a standard tool for assaying gene function in RNAi knockdown screens and protein localization studies in eukaryotic systems. Similar high throughput studies can be attempted in prokaryotes, though the difficulties surrounding work at the diffraction limit pose challenges, and targeting essential genes in a high throughput way can be difficult. Here we will discuss efforts to make live-cell fluorescent microscopy based experiments using genetically encoded fluorescent reporters an automated, high throughput, and quantitative endeavor amenable to systems-level experiments in bacteria. We emphasize a quantitative data reduction approach, using simulation to help develop biologically relevant cell measurements that completely characterize the cell image. We give an example of how this type of data can be directly exploited by statistical learning algorithms to discover functional pathways.
The diffraction limit makes high-throughput fluorescence microscopy more challenging in prokaryotes, but approaches such as quantitative data reduction now allow systems-level analysis of bacteria by this technique.
PMCID: PMC2908775  PMID: 20591990
4.  The essential genome of a bacterium 
This study reports the essential Caulobacter genome at 8 bp resolution determined by saturated transposon mutagenesis and high-throughput sequencing. This strategy is applicable to full genome essentiality studies in a broad class of bacterial species.
The essential Caulobacter genome was determined at 8 bp resolution using hyper-saturated transposon mutagenesis coupled with high-throughput sequencing.Essential protein-coding sequences comprise 90% of the essential genome; the remaining 10% comprising essential non-coding RNA sequences, gene regulatory elements and essential genome replication features.Of the 3876 annotated open reading frames (ORFs), 480 (12.4%) were essential ORFs, 3240 (83.6%) were non-essential ORFs and 156 (4.0%) were ORFs that severely impacted fitness when mutated.The essential elements are preferentially positioned near the origin and terminus of the Caulobacter chromosome.This high-resolution strategy is applicable to high-throughput, full genome essentiality studies and large-scale genetic perturbation experiments in a broad class of bacterial species.
The regulatory events that control polar differentiation and cell-cycle progression in the bacterium Caulobacter crescentus are highly integrated, and they have to occur in the proper order (McAdams and Shapiro, 2011). Components of the core regulatory circuit are largely known. Full discovery of its essential genome, including non-coding, regulatory and coding elements, is a prerequisite for understanding the complete regulatory network of this bacterial cell. We have identified all the essential coding and non-coding elements of the Caulobacter chromosome using a hyper-saturated transposon mutagenesis strategy that is scalable and can be readily extended to obtain rapid and accurate identification of the essential genome elements of any sequenced bacterial species at a resolution of a few base pairs.
We engineered a Tn5 derivative transposon (Tn5Pxyl) that carries at one end an inducible outward pointing Pxyl promoter (Christen et al, 2010). We showed that this transposon construct inserts into the genome randomly where it can activate or disrupt transcription at the site of integration, depending on the insertion orientation. DNA from hundred of thousands of transposon insertion sites reading outward into flanking genomic regions was parallel PCR amplified and sequenced by Illumina paired-end sequencing to locate the insertion site in each mutant strain (Figure 1). A single sequencing run on DNA from a mutagenized cell population yielded 118 million raw sequencing reads. Of these, >90 million (>80%) read outward from the transposon element into adjacent genomic DNA regions and the insertion site could be mapped with single nucleotide resolution. This yielded the location and orientation of 428 735 independent transposon insertions in the 4-Mbp Caulobacter genome.
Within non-coding sequences of the Caulobacter genome, we detected 130 non-disruptable DNA segments between 90 and 393 bp long in addition to all essential promoter elements. Among 27 previously identified and validated sRNAs (Landt et al, 2008), three were contained within non-disruptable DNA segments and another three were partially disruptable, that is, insertions caused a notable growth defect. Two additional small RNAs found to be essential are the transfer-messenger RNA (tmRNA) and the ribozyme RNAseP (Landt et al, 2008). In addition to the 8 non-disruptable sRNAs, 29 out of the 130 intergenic essential non-coding sequences contained non-redundant tRNA genes; duplicated tRNA genes were non-essential. We also identified two non-disruptable DNA segments within the chromosomal origin of replication. Thus, we resolved essential non-coding RNAs, tRNAs and essential replication elements within the origin region of the chromosome. An additional 90 non-disruptable small genome elements of currently unknown function were identified. Eighteen of these are conserved in at least one closely related species. Only 2 could encode a protein of over 50 amino acids.
For each of the 3876 annotated open reading frames (ORFs), we analyzed the distribution, orientation, and genetic context of transposon insertions. There are 480 essential ORFs and 3240 non-essential ORFs. In addition, there were 156 ORFs that severely impacted fitness when mutated. The 8-bp resolution allowed a dissection of the essential and non-essential regions of the coding sequences. Sixty ORFs had transposon insertions within a significant portion of their 3′ region but lacked insertions in the essential 5′ coding region, allowing the identification of non-essential protein segments. For example, transposon insertions in the essential cell-cycle regulatory gene divL, a tyrosine kinase, showed that the last 204 C-terminal amino acids did not impact viability, confirming previous reports that the C-terminal ATPase domain of DivL is dispensable for viability (Reisinger et al, 2007; Iniesta et al, 2010). In addition, we found that 30 out of 480 (6.3%) of the essential ORFs appear to be shorter than the annotated ORF, suggesting that these are probably mis-annotated.
Among the 480 ORFs essential for growth on rich media, there were 10 essential transcriptional regulatory proteins, including 5 previously identified cell-cycle regulators (McAdams and Shapiro, 2003; Holtzendorff et al, 2004; Collier and Shapiro, 2007; Gora et al, 2010; Tan et al, 2010) and 5 uncharacterized predicted transcription factors. In addition, two RNA polymerase sigma factors RpoH and RpoD, as well as the anti-sigma factor ChrR, which mitigates rpoE-dependent stress response under physiological growth conditions (Lourenco and Gomes, 2009), were also found to be essential. Thus, a set of 10 transcription factors, 2 RNA polymerase sigma factors and 1 anti-sigma factor are the core essential transcriptional regulators for growth on rich media. To further characterize the core components of the Caulobacter cell-cycle control network, we identified all essential regulatory sequences and operon transcripts. Altogether, the 480 essential protein-coding and 37 essential RNA-coding Caulobacter genes are organized into operons such that 402 individual promoter regions are sufficient to regulate their expression. Of these 402 essential promoters, the transcription start sites (TSSs) of 105 were previously identified (McGrath et al, 2007).
The essential genome features are non-uniformly distributed on the Caulobacter genome and enriched near the origin and the terminus regions. In contrast, the chromosomal positions of the published E. coli essential coding sequences (Rocha, 2004) are preferentially located at either side of the origin (Figure 4A). This indicates that there are selective pressures on chromosomal positioning of some essential elements (Figure 4A).
The strategy described in this report could be readily extended to quickly determine the essential genome for a large class of bacterial species.
Caulobacter crescentus is a model organism for the integrated circuitry that runs a bacterial cell cycle. Full discovery of its essential genome, including non-coding, regulatory and coding elements, is a prerequisite for understanding the complete regulatory network of a bacterial cell. Using hyper-saturated transposon mutagenesis coupled with high-throughput sequencing, we determined the essential Caulobacter genome at 8 bp resolution, including 1012 essential genome features: 480 ORFs, 402 regulatory sequences and 130 non-coding elements, including 90 intergenic segments of unknown function. The essential transcriptional circuitry for growth on rich media includes 10 transcription factors, 2 RNA polymerase sigma factors and 1 anti-sigma factor. We identified all essential promoter elements for the cell cycle-regulated genes. The essential elements are preferentially positioned near the origin and terminus of the chromosome. The high-resolution strategy used here is applicable to high-throughput, full genome essentiality studies and large-scale genetic perturbation experiments in a broad class of bacterial species.
PMCID: PMC3202797  PMID: 21878915
functional genomics; next-generation sequencing; systems biology; transposon mutagenesis
5.  Caulobacter PopZ forms a polar subdomain dictating sequential changes in pole composition and function 
Molecular microbiology  2010;76(1):173-189.
The bacterium Caulobacter crescentus has morphologically and functionally distinct cell poles that undergo sequential changes during the cell cycle. We show that the PopZ oligomeric network forms polar ribosome exclusion zones that change function during cell cycle progression. The parS/ParB chromosomal centromere is tethered to PopZ at one pole prior to the initiation of DNA replication. During polar maturation, the PopZ-centromere tether is broken, and the PopZ zone at that pole then switches function to act as a recruitment factor for the ordered addition of multiple proteins that promote the transformation of the flagellated pole into a stalked pole. Stalked pole assembly, in turn, triggers the initiation of chromosome replication, which signals the formation of a new PopZ zone at the opposite cell pole, where it functions to anchor the newly duplicated centromere that has traversed the long axis of the cell. We propose that pole-specific control of PopZ function co-ordinates polar development and cell cycle progression by enabling independent assembly and tethering activities at the two cell poles.
PMCID: PMC2935252  PMID: 20149103
6.  A method for detecting and correcting feature misidentification on expression microarrays 
BMC Genomics  2004;5:64.
Much of the microarray data published at Stanford is based on mouse and human arrays produced under controlled and monitored conditions at the Brown and Botstein laboratories and at the Stanford Functional Genomics Facility (SFGF). Nevertheless, as large datasets based on the Stanford Human array began to accumulate, a small but significant number of discrepancies were detected that required a serious attempt to track down the original source of error. Due to a controlled process environment, sufficient data was available to accurately track the entire process leading to up to the final expression data. In this paper, we describe our statistical methods to detect the inconsistencies in microarray data that arise from process errors, and discuss our technique to locate and fix these errors.
To date, the Brown and Botstein laboratories and the Stanford Functional Genomics Facility have together produced 40,000 large-scale (10–50,000 feature) cDNA microarrays. By applying the heuristic described here, we have been able to check most of these arrays for misidentified features, and have been able to confidently apply fixes to the data where needed. Out of the 265 million features checked in our database, problems were detected and corrected on 1.3 million of them.
Process errors in any genome scale high throughput production regime can lead to subsequent errors in data analysis. We show the value of tracking multi-step high throughput operations by using this knowledge to detect and correct misidentified data on gene expression microarrays.
PMCID: PMC521069  PMID: 15357875
7.  Universal Reference RNA as a standard for microarray experiments 
BMC Genomics  2004;5:20.
Obtaining reliable and reproducible two-color microarray gene expression data is critically important for understanding the biological significance of perturbations made on a cellular system. Microarray design, RNA preparation and labeling, hybridization conditions and data acquisition and analysis are variables difficult to simultaneously control. A useful tool for monitoring and controlling intra- and inter-experimental variation is Universal Reference RNA (URR), developed with the goal of providing hybridization signal at each microarray probe location (spot). Measuring signal at each spot as the ratio of experimental RNA to reference RNA targets, rather than relying on absolute signal intensity, decreases variability by normalizing signal output in any two-color hybridization experiment.
Human, mouse and rat URR (UHRR, UMRR and URRR, respectively) were prepared from pools of RNA derived from individual cell lines representing different tissues. A variety of microarrays were used to determine percentage of spots hybridizing with URR and producing signal above a user defined threshold (microarray coverage). Microarray coverage was consistently greater than 80% for all arrays tested. We confirmed that individual cell lines contribute their own unique set of genes to URR, arguing for a pool of RNA from several cell lines as a better configuration for URR as opposed to a single cell line source for URR. Microarray coverage comparing two separately prepared batches each of UHRR, UMRR and URRR were highly correlated (Pearson's correlation coefficients of 0.97).
Results of this study demonstrate that large quantities of pooled RNA from individual cell lines are reproducibly prepared and possess diverse gene representation. This type of reference provides a standard for reducing variation in microarray experiments and allows more reliable comparison of gene expression data within and between experiments and laboratories.
PMCID: PMC394318  PMID: 15113400
microarray; universal reference RNA; standardization.
8.  Gene Expression Patterns in Ovarian Carcinomas 
Molecular Biology of the Cell  2003;14(11):4376-4386.
We used DNA microarrays to characterize the global gene expression patterns in surface epithelial cancers of the ovary. We identified groups of genes that distinguished the clear cell subtype from other ovarian carcinomas, grade I and II from grade III serous papillary carcinomas, and ovarian from breast carcinomas. Six clear cell carcinomas were distinguished from 36 other ovarian carcinomas (predominantly serous papillary) based on their gene expression patterns. The differences may yield insights into the worse prognosis and therapeutic resistance associated with clear cell carcinomas. A comparison of the gene expression patterns in the ovarian cancers to published data of gene expression in breast cancers revealed a large number of differentially expressed genes. We identified a group of 62 genes that correctly classified all 125 breast and ovarian cancer specimens. Among the best discriminators more highly expressed in the ovarian carcinomas were PAX8 (paired box gene 8), mesothelin, and ephrin-B1 (EFNB1). Although estrogen receptor was expressed in both the ovarian and breast cancers, genes that are coregulated with the estrogen receptor in breast cancers, including GATA-3, LIV-1, and X-box binding protein 1, did not show a similar pattern of coexpression in the ovarian cancers.
PMCID: PMC266758  PMID: 12960427

Results 1-8 (8)