Molecular mechanisms that distinguish TFIID housekeeping from regulatable SAGA promoters

An important distinction is frequently made between constitutively expressed housekeeping genes versus regulated genes. Although generally characterized by different DNA elements, chromatin architecture and cofactors, it is not known to what degree promoter classes strictly follow regulatability rules and which molecular mechanisms dictate such differences. We show that SAGA-dominated/wTATA-box promoters are more responsive to changes in the amount of activator, even compared to TFIID/TATA-like promoters that depend on the same activator Hsf1. Regulatability is therefore an inherent property of promoter class. Further analyses show that SAGA/TATA-box promoters are more dynamic because TATA-binding protein recruitment through SAGA is susceptible to removal by Mot1. In addition, the nucleosome configuration upon activator depletion shifts on SAGA/TATA-box promoters and seems less amenable to preinitiation complex formation. The results explain the fundamental difference between housekeeping and regulatable genes, revealing an additional facet of combinatorial control: an activator can elicit a different response dependent on core promoter class

Accuracy of Protein-Protein Binding Sites in High-Throughput Template-Based Modeling

The accuracy of protein structures, particularly their binding sites, is essential for the success of modeling protein complexes. Computationally inexpensive methodology is required for genome-wide modeling of such structures. For systematic evaluation of potential accuracy in high-throughput modeling of binding sites, a statistical analysis of target-template sequence alignments was performed for a representative set of protein complexes. For most of the complexes, alignments containing all residues of the interface were found. The full interface alignments were obtained even in the case of poor alignments where a relatively small part of the target sequence (as low as 40%) aligned to the template sequence, with a low overall alignment identity (<30%). Although such poor overall alignments might be considered inadequate for modeling of whole proteins, the alignment of the interfaces was strong enough for docking. In the set of homology models built on these alignments, one third of those ranked 1 by a simple sequence identity criteria had RMSD<5 Å, the accuracy suitable for low-resolution template free docking. Such models corresponded to multi-domain target proteins, whereas for single-domain proteins the best models had 5 Å<RMSD<10 Å, the accuracy suitable for less sensitive structure-alignment methods. Overall, ∼50% of complexes with the interfaces modeled by high-throughput techniques had accuracy suitable for meaningful docking experiments. This percentage will grow with the increasing availability of co-crystallized protein-protein complexes

An organoid biobank for childhood kidney cancers that captures disease and tissue heterogeneity

Kidney tumours are among the most common solid tumours in children, comprising distinct subtypes differing in many aspects, including cell-of-origin, genetics, and pathology. Pre-clinical cell models capturing the disease heterogeneity are currently lacking. Here, we describe the first paediatric cancer organoid biobank. It contains tumour and matching normal kidney organoids from over 50 children with different subtypes of kidney cancer, including Wilms tumours, malignant rhabdoid tumours, renal cell carcinomas, and congenital mesoblastic nephromas. Paediatric kidney tumour organoids retain key properties of native tumours, useful for revealing patient-specific drug sensitivities. Using single cell RNA-sequencing and high resolution 3D imaging, we further demonstrate that organoid cultures derived from Wilms tumours consist of multiple different cell types, including epithelial, stromal and blastemal-like cells. Our organoid biobank captures the heterogeneity of paediatric kidney tumours, providing a representative collection of well-characterised models for basic cancer research, drug-screening and personalised medicine

Gcn4 misregulation reveals a direct role for the evolutionary conserved EKC/KEOPS in the t6A modification of tRNAs

The EKC/KEOPS complex is universally conserved in Archaea and Eukarya and has been implicated in several cellular processes, including transcription, telomere homeostasis and genomic instability. However, the molecular function of the complex has remained elusive so far. We analyzed the transcriptome of EKC/KEOPS mutants and observed a specific profile that is highly enriched in targets of the Gcn4p transcriptional activator. GCN4 expression was found to be activated at the translational level in mutants via the defective recognition of the inhibitory upstream ORFs (uORFs) present in its leader. We show that EKC/KEOPS mutants are defective for the N6-threonylcarbamoyl adenosine modification at position 37 (t6A37) of tRNAs decoding ANN codons, which affects initiation at the inhibitory uORFs and provokes Gcn4 de-repression. Structural modeling reveals similarities between Kae1 and bacterial enzymes involved in carbamoylation reactions analogous to t6A37 formation, supporting a direct role for the EKC in tRNA modification. These findings are further supported by strong genetic interactions of EKC mutants with a translation initiation factor and with threonine biosynthesis genes. Overall, our data provide a novel twist to understanding the primary function of the EKC/KEOPS and its impact on several essential cellular functions like transcription and telomere homeostasis

Tumor to normal single-cell mRNA comparisons reveal a pan-neuroblastoma cancer cell

Neuroblastoma is a childhood cancer that resembles developmental stages of the neural crest. It is not established what developmental processes neuroblastoma cancer cells represent. Here, we sought to reveal the phenotype of neuroblastoma cancer cells by comparing cancer (n = 19,723) with normal fetal adrenal single-cell transcriptomes (n = 57,972). Our principal finding was that the neuroblastoma cancer cell resembled fetal sympathoblasts, but no other fetal adrenal cell type. The sympathoblastic state was a universal feature of neuroblastoma cells, transcending cell cluster diversity, individual patients, and clinical phenotypes. We substantiated our findings in 650 neuroblastoma bulk transcriptomes and by integrating canonical features of the neuroblastoma genome with transcriptional signals. Overall, our observations indicate that a pan-neuroblastoma cancer cell state exists, which may be attractive for novel immunotherapeutic and targeted avenues

Hydrophobic patches on protein surfaces

Hydrophobicity is a prime determinant of the structure and function of proteins. It is the driving force behind the folding of soluble proteins, and when exposed on the surface, it is frequently involved in recognition and binding of ligands and other proteins. The energetic cost of exposing hydrophobic surface is proportional to its area, and the question arises to what extent proteins can tolerate large hydrophobic patches on their surfaces. The current thesis is a study into such patches. Chapter 1 provides a general introduction into protein surface hydrophobicity. Chapter 2 describes a numerical algorithm for calculating the solvent accessible surface area. It samples the protein surface in Shrake & Rupley fashion: representing atoms as spherical distributions of points and summing the points that are not buried by any atoms. A number of optimization strategies is applied, yielding an exceptionally fast method. The quality of spherical point distributions is assessed, and a novel, optimal tessellation of the unit sphere is found. The accessible surface calculation method developed in Chapter 2 forms the basis of the hydrophobic patch detection algorithm called QUILT, presented in Chapter 3. The assumption is that hydrophobic surface area is synonymous with solvent accessible carbon and sulfur atoms. Connecting contiguous apolar atoms is not enough to delineate hydrophobic patches, because the relatively strong hydrophobicity of the protein surface (around 60%) results in one large hydrophobic surface. This surface spans the entire protein, and is dotted with polar 'islands' formed by the hydrophilic atoms, with hydrophobic connections through variously sized 'channels' between these islands. To delineate the hydrophobic patches, the channels are closed off by temporarily expanding the solvent-accessible polar atoms. This way, the hydrophobic surface neatly divides into proper patches which are subsequently identified, and adjacent surface area lost due to the polar expansion is added back to the patches thus obtained. Only the largest patches, having sizes exceeding expectation (based on randomizing the protein's surface), are deemed meaningful. The method is applied to a small number of structures to demonstrate the validity and utility of the method. In Chapter 4, the QUILT method is applied to a large sample of monomeric proteins, in order to survey general trends in the distribution of patch sizes on proteins. The largest patch on each individual protein averages around 400 Å2, but can range from 200 to 1200 Å2. Interestingly, these areas do not correlate with the sizes of the proteins, and only weakly with their apolar surface fraction. Trends regarding patch size distribution, amino acid composition and preference, sequential vicinity, secondary structure and mobility are discussed as well. Chapter 5 is devoted to a survey similar to that described in Chapter 4, but here, the interfaces of obligate oligomeric proteins are studied. As before, trends regarding amino acid composition and preference and patch size distribution are described. The largest or second largest patch on the accessible surface of the entire subunit was involved in multimeric interfaces in 90% of the cases, in agreement with interfaces being generally more hydrophobic than the rest of the protein surface. However, hydrophobic patches are not complementary: they are not preferentially in contact across associating subunits. This is perhaps surprising, but is to be expected, because the free energy of subunit association, as far as the hydrophobic patches are concerned, is largely due to the shielding of apolar area from the solvent, rather than from gaining hydrophobic contacts. To gain insight into the dynamic behaviour of hydrophobic patches, QUILT is applied to molecular dynamics simulations of three different protein structures. This is the subject of Chapter 6. The analysis requires an additional method to relate QUILT-patches across time frames of the trajectory, which is described as well. The resulting patch runs show that the area fluctuations are considerable, at around 25% of their size. The most frequently occurring mean patch size is approximately 50 Å2, but can reach around 400 Å2. An uninterrupted patch run can last up to 150 picoseconds, but, owing to protein mobility, is generally much shorter at around 4 ps. There is no clear relation between patch run durations and their average size, but long-lasting patch runs have smaller fluctuations. Although the formalism would allow this, the patches do not 'wander' over the protein surface, indicating that they are genuine surface features. When the patch runs are clustered, the truly persistent patches called recurrent patches are obtained. Only about 25% of them have a strong 'liveness', that is, are represented by an actual patch run most of the time. In amicyanin, the method detects the hydrophobic patch known to be involved in the binding of methylamine dehydrogenase. In phospholipase A2, a large persistent patch consisting of Leu58 and Phe94 is found, the likely functional relevance of which appears to be novel