The binding of Src-homology 2 (SH2) domains to phosphotyrosine (pY) sites is critical for the autoinhibition and substrate recognition of the eight Src family kinases (SFKs). The high sequence conservation of the 120 human SH2 domains poses a significant challenge to selectively perturb the interactions of even the SFK SH2 family against the rest of the SH2 domains. We have developed synthetic binding proteins, termed monobodies, for six of the SFK SH2 domains with nanomolar affinity. Most of these monobodies competed with pY ligand binding and showed strong selectivity for either the SrcA (Yes, Src, Fyn, Fgr) or SrcB subgroup (Lck, Lyn, Blk, Hck). Interactome analysis of intracellularly expressed monobodies revealed that they bind SFKs but no other SH2-containing proteins. Three crystal structures of monobody–SH2 complexes unveiled different and only partly overlapping binding modes, which rationalized the observed selectivity and enabled structure-based mutagenesis to modulate inhibition mode and selectivity. In line with the critical roles of SFK SH2 domains in kinase autoinhibition and T-cell receptor signaling, monobodies binding the Src and Hck SH2 domains selectively activated respective recombinant kinases, whereas an Lck SH2-binding monobody inhibited proximal signaling events downstream of the T-cell receptor complex. Our results show that SFK SH2 domains can be targeted with unprecedented potency and selectivity using monobodies. They are excellent tools for dissecting SFK functions in normal development and signaling and to interfere with aberrant SFK signaling networks in cancer cells.

Numerous age‐related human diseases have been associated with deficiencies in cellular energy production. Moreover, genetic alterations resulting in mitochondrial dysfunction are the cause of inheritable disorders commonly known as mitochondrial diseases. Many of these deficiencies have been directly or indirectly linked to deficits in mitochondrial gene expression. Transcription is an essential step in gene expression and elucidating the molecular mechanisms involved in this process is critical for understanding defects in energy production. For the past five decades, substantial efforts have been invested in the field of mitochondrial transcription. These efforts have led to the discovery of the main protein factors responsible for transcription as well as to a basic mechanistic understanding of the transcription process. They have also revealed various mechanisms of transcriptional regulation as well as the links that exist between the transcription process and downstream processes of RNA maturation. Here, we review the knowledge gathered in early mitochondrial transcription studies and focus on recent findings that shape our current understanding of mitochondrial transcription, posttranscriptional processing, as well as transcriptional regulation in mammalian systems.

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Viral vector-based gene therapies and vaccines require accurate characterization of capsid species. The current gold standard for assessing capsid loading of adeno-associated virus (AAV) is sedimentation velocity analytical ultracentrifugation (SV-AUC). However, routine SV-AUC analysis is often size-limited, especially without the use of advanced techniques (e.g., gravitational-sweep) or when acquiring the multiwavelength data needed for assessing the loading fraction of viral vectors, and requires analysis by specialized software packages. Density gradient equilibrium AUC (DGE-AUC) is a highly simplified analytical method that provides high-resolution separation of biologics of different densities (e.g., empty and full viral capsids). The analysis required is significantly simpler than SV-AUC, and larger viral particles such as adenovirus (AdV) are amenable to characterization by DGE-AUC using cesium chloride gradients. This method provides high-resolution data with significantly less sample (estimated 56-fold improvement in sensitivity compared to SV-AUC). Multiwavelength analysis can also be used without compromising data quality. Finally, DGE-AUC is serotype-agnostic and amenable to intuitive interpretation and analysis (not requiring specialized AUC software). Here, we present suggestions for optimizing DGE-AUC methods and demonstrate a high-throughput AdV packaging analysis with the AUC, running as many as 21 samples in 80 min.