Fluorescent protein (FP) tagging is widely used in imaging experiments to investigate the subcellular distribution of proteins. However, because the fluorescence of most FP chromophores is quenched upon their protonation, their fluorescence intensities are dependent on their pKas and on the environmental pH. Thus, the concentration of a protein tagged with EGFP (pKa = 6.0) is dramatically underestimated in the lysosomal lumen (pH ~4.7) compared to that of the same protein tagged with mCherry (pKa = 4.5). In this study, we examined the effect of differential FP tagging on the apparent subcellular distribution of several proteins that reside on the cytoplasmic surfaces of secretory/endocytic organelles. Due to the presumed uniformity of cytoplasmic conditions (pH ~7.2–7.4), we expected to find essentially complete overlap of fluorescent signals, regardless of the nature of the fused FP. However, we were surprised to observe significant discrepancies in the apparent distributions of a subset of proteins tagged with EGFP vs. mCherry (Pearson’s correlation coefficients of about 0.80). These discrepancies were not evident when comparing proteins tagged with mCherry vs. other FPs with low pKas (e.g., mTurquoise (pKa = 4.5), mCerulean (pKa = 3.2)) (Pearson’s correlation coefficients of about 0.90–0.95). Our results suggest that FP tags may be sensitive to the microenvironments on the cytoplasmic surfaces of different organelles.

The matrix (MA) domain of the Gag polyprotein is critical for directing retroviral assembly at the plasma membrane (PM), yet the determinants mediating human T-cell leukemia virus type 1 (HTLV-1) Gag targeting remain incompletely defined. While Gag myristoylation and basic residue-mediated electrostatic interactions are known to be crucial for Gag-PM interactions, recent evidence with HTLV-1 MA has implicated limited dependence on specific lipid headgroup recognition for Gag interaction with the PM. Here, we have analyzed the role of non-basic residues in HTLV-1 MA in membrane interactions and particle assembly. We identified several residues (i.e., L19, D42, S70, and L71) that were essential for Gag targeting to the PM, where mutation of these amino acid residues led to Gag targeting to internal locations that colocalized with late endosomal markers. Mutation of L19 and D42 was found to alter the MA structure. Taken together, these data indicate that mutation of MA non-basic amino acid residues affected particle production and also led to Gag localization to internal membranes that colocalized with late endosomal markers. These observations indicate that non-basic residues play an important role in efficient particle assembly and release of HTLV-1 from cells.

Human immunodeficiency virus type 1 (HIV-1) particle assembly is driven by the Gag structural polyprotein and is a crucial step in the production of new virus particles. Elucidating the details of this process is necessary to fully understand the virus replication cycle. Real-time measurements of virus particle biogenesis in living cells have proved challenging, and most of our knowledge of this process to date has come from total internal fluorescence microscopy of labeled Gag at the bottom plasma membrane (PM) of adherent cells. While the glass coverslip adjacent to the bottom PM renders this an artificial environment, fluorescence measurements at the more physiologically relevant top PM are challenging due to the three-dimensional (3D) profile at the top PM as well as the large, structured background fluorescence that arises due to cytoplasmic, unassembled Gag protein. Here, we describe an approach to 3D localization microscopy and analysis to address the challenges associated with imaging virus assembly at the top PM in live cells. Specifically, we have employed the double helix point spread function for 3D imaging with an extended depth of field combined with a deep learning pipeline to analyze images that contain heterogeneous structured backgrounds. We demonstrate the power of this approach by measuring virus assembly at the top PM of adherent cells in 3D fluorescence microscopy and observe intriguing differences in the assembly kinetics and HIV-1 Gag puncta mobility between the adherent bottom PM and the nonadherent top PM.

Fluorescence correlation spectroscopy (FCS) is a powerful method to measure concentration, mobility, and stoichiometry in solution and in living cells, but quantitative analysis of FCS data remains challenging due to the correlated noise in the autocorrelation function (ACF) of FCS. We demonstrate here that least-squares fitting of the conventional ACF is incompatible with the χ2 goodness-of-fit test and systematically underestimates the true fit parameter uncertainty. To overcome this challenge, a simple method to fit the ACF is introduced that allows proper calculation of goodness-of-fit statistics and that provides more tightly constrained parameter estimates than the conventional least-squares fitting method, achieving the theoretical minimum uncertainty. Because this method requires significantly more data than the standard method, we further introduce an approximate method that requires fewer data. We demonstrate both these new methods using experiments and simulations of diffusion. Finally, we apply our method to FCS data of the peripheral membrane protein HRas, which has a slow-diffusing membrane-bound population and a fast-diffusing cytoplasmic population. Despite the order-of-magnitude difference of the diffusion times, conventional FCS fails to reliably resolve the two species, whereas the new method identifies the correct model and provides robust estimates of the fit parameters for both species.

GABARAP is a member of the ATG8 family of ubiquitin-like autophagy related proteins. It was initially discovered as a facilitator of GABA-A receptor translocation to the plasma membrane and has since been shown to promote the intracellular transport of a variety of other proteins under non-autophagic conditions. We and others have shown that GABARAP interacts with the Type II phosphatidylinositol 4-kinase, PI4K2A, and that this interaction is important for autophagosome-lysosome fusion. Here, we identify a 7-amino acid segment within the PI4K2A catalytic domain that contains the GABARAP interaction motif (GIM). This segment resides in an exposed loop that is not conserved in the other mammalian Type II PI 4-kinase, PI4K2B, explaining the specificity of GABARAP binding to the PI4K2A isoform. Mutation of the PI4K2A GIM inhibits GABARAP binding and PI4K2A-mediated recruitment of cytosolic GABARAP to subcellular organelles. We further show that GABARAP binds to mono-phosphorylated phosphoinositides, PI3P, PI4P, and PI5P, raising the possibility that these lipids contribute to the binding energies that drive GABARAP-protein interactions on membranes.

Arc (also known as Arg3.1) is an activity-dependent immediate early gene product enriched in neuronal dendrites. Arc plays essential roles in long-term potentiation, long-term depression, and synaptic scaling. Although its mechanisms of action in these forms of synaptic plasticity are not completely well established, the activities of Arc include the remodeling of the actin cytoskeleton, the facilitation of AMPA receptor (AMPAR) endocytosis, and the regulation of the transcription of AMPAR subunits. In addition, Arc has sequence and structural similarity to retroviral Gag proteins and self-associates into virus-like particles that encapsulate mRNA and perhaps other cargo for intercellular transport. Each of these activities is likely to be influenced by Arc’s reversible self-association into multiple oligomeric species. Here, we used mass photometry to show that Arc exists predominantly as monomers, dimers, and trimers at approximately 20 nM concentration in vitro. Fluorescence fluctuation spectroscopy revealed that Arc is almost exclusively present as low-order (monomer to tetramer) oligomers in the cytoplasm of living cells, over a 200 nM to 5 μM concentration range. We also confirmed that an α-helical segment in the N-terminal domain contains essential determinants of Arc’s self-association.

The cell cortex plays a crucial role in cell mechanics, signaling, and development. However, little is known about the influence of the cortical meshwork on the spatial distribution of cytoplasmic biomolecules. Here, we describe a fluorescence microscopy method with the capacity to infer the intracellular distribution of labeled biomolecules with subresolution accuracy. Unexpectedly, we find that RNA binding proteins are partially excluded from the cytoplasmic volume adjacent to the plasma membrane that corresponds to the actin cortex. Complementary diffusion measurements of RNA-protein complexes suggest that a rudimentary model based on excluded volume interactions can explain this partitioning effect. Our results suggest the actin cortex meshwork may play a role in regulating the biomolecular content of the volume immediately adjacent to the plasma membrane.

Assembly of human T-cell leukemia virus type 1 (HTLV-1) particles is initiated by the trafficking of virally encoded Gag polyproteins to the inner leaflet of the plasma membrane (PM). Gag-PM interactions are mediated by the matrix (MA) domain, which contains a myristoyl group (myr) and a basic patch formed by lysine and arginine residues. For many retroviruses, Gag-PM interactions are mediated by phosphatidylinositol 4,5-bisphosphate [PI(4,5)P2]; however, previous studies suggested that HTLV-1 Gag-PM interactions and therefore virus assembly are less dependent on PI(4,5)P2. We have recently shown that PI(4,5)P2 binds directly to HTLV-1 unmyristoylated MA [myr(-)MA] and that myr(-)MA binding to membranes is significantly enhanced by inclusion of phosphatidylserine (PS) and PI(4,5)P2. Herein, we employed structural, biophysical, biochemical, mutagenesis, and cell-based assays to identify residues involved in MA-membrane interactions. Our data revealed that the lysine-rich motif (Lys47, Lys48, and Lys51) constitutes the primary PI(4,5)P2-binding site. Furthermore, we show that arginine residues 3, 7, 14 and 17 located in the unstructured N-terminus are essential for MA binding to membranes containing PS and/or PI(4,5)P2. Substitution of lysine and arginine residues severely attenuated virus-like particle production, but only the lysine residues could be clearly correlated with reduced PM binding. These results support a mechanism by which HTLV-1 Gag targeting to the PM is mediated by a trio engagement of the myr group, Arg-rich and Lys-rich motifs. These findings advance our understanding of a key step in retroviral particle assembly.

Chemical and mechanical nuclear-cytoplasmic communication across the nuclear envelope (NE) is largely mediated by the nuclear pore complex (NPC) and the linker of nucleoskeleton and cytoskeleton (LINC) complex, respectively. While NPC and LINC complex assembly are functionally related, the mechanisms responsible for this relationship remain poorly understood. Here, we investigated how the luminal ATPases associated with various cellular activities (AAA+) protein torsinA (TA) promotes NPC and LINC complex assembly using fluorescence fluctuation spectroscopy (FFS), quantitative photobleaching analyses, and functional cellular assays. We report that TA controls LINC complex-dependent nuclear-cytoskeletal coupling as a soluble hexameric AAA+ protein and interphase NPC biogenesis (iNPCb) as a membrane-associated helical polymer. These findings help resolve the conflicting models of TA function that were recently proposed based on in vitro structural studies. Our results will enable future studies of the role of defective nuclear cytoplasmic communication in DYT1 dystonia and other diseases caused by mutations in TA.

Degradation of autophagosomal cargo requires the tethering and fusion of autophagosomes with lysosomes that is mediated by the scaffolding protein autophagy related 14 (ATG14). Here, we report that phosphatidylinositol 4-kinase 2A (PI4K2A) generates a pool of phosphatidylinositol 4-phosphate (PI4P) that facilitates the recruitment of ATG14 to mature autophagosomes. We also show that PI4K2A binds to ATG14, suggesting that PI4P may be synthesized in situ in the vicinity of ATG14. Impaired targeting of ATG14 to autophagosomes in PI4K2A-depleted cells is rescued by the introduction of PI4P but not its downstream product phosphatidylinositol 4,5-bisphosphate (PI(4,5)P2). Thus, PI4P and PI(4,5)P2 have independent functions in late-stage autophagy. These results provide a mechanism to explain prior studies indicating that PI4K2A and its product PI4P are necessary for autophagosome-lysosome fusion.

The experimental autocorrelation fu nction of fluorescence correlation spectroscopy calculated from finite-length data is a biased estimator of the theoretical correlation function. This study presents a new theoretical framework that explicitly accounts for the data length to allow for unbiased analysis of experimental autocorrelation functions. To validate our theory, we applied it to experiments and simulations of diffusion and characterized the accuracy and precision of the resulting parameter estimates. Because measurements in living cells are often affected by instabilities of the fluorescence signal, autocorrelation functions are typically calculated on segmented data to improve their robustness. Our reformulated theory extends the range of usable segment times down to timescales approaching the diffusion time. This flexibility confers unique advantages for live-cell data that contain intensity variations and instabilities. We describe several applications of short segmentation to analyze data contaminated with unwanted fluctuations, drifts, or spikes in the intensity that are not suited for conventional fluorescence correlation analysis. These results demonstrate the potential of our theoretical framework to significantly expand the experi-mental systems accessible to fluorescence correlation spectroscopy.

Fluorescence correlation spectroscopy (FCS) determines mobility and stoichiometry of fluorescent species through statistical analysis of the autocorrelation of the fluorescence intensity signal. This information complements standard biochemical assays by allowing such information to be measured noninvasively in living cells. Unfortunately, autocorrelation analysis assumes stationarity and ergodicity of signals, which are conditions that are not always possible to obtain in living cells. For example, fluorescence correlation measurements at the nuclear envelope of living cells encounter a slow volume undulation process, which is superimposed on the diffusive fluctuations arising from motion of the fluorescent tag. This situation requires very long data acquisition times to ensure proper sampling of the slow process, which is difficult to achieve in live cell measurements. It would be advantageous to conduct short measurements that only sample the diffusive process. However, standard autocorrelation analysis does not allow choosing short segments to consider only the fluctuation of interest, because it assumes a data segment that is very long compared to the slowest timescale of fluctuations in the system. Here we present an analytical fluorescence correlation method that accounts for finite data segment length and recovers unbiased mobility and stoichiometry estimates from short data segments. We demonstrate this method using simulations and experimental data taken at the nuclear envelope of a living cell. Finally, we explore the possibility of fitting multiple data segment lengths simultaneously using this method to increase the resolving power of fluorescence correlation analysis. This work has been supported by grants from the National Institutes of Health (R01 GM098550, GM064589, and GM124279).

Point spread function engineering techniques have extended the axial range accessible to fluorescence microscopy by simple modifications to the optical path of a microscope. A particularly promising engineered PSF is the double helix PSF (DHPSF), which provides an axial range of over 2 μm. This extended depth allows sub-diffraction localization of point sources in 3D across an axial range approaching the typical thickness of mammalian adherent cells. Thus, DHPSF is not only attractive for PALM-style superresolution experiments but also for tracking small punctate structures in cells. Still, data analysis of DHPSF images presents a challenge because no analytic form of the DHPSF exists. This difficulty has been addressed previously by using heuristic functions for fitting or interpolations of calibration scans of fluorescent beads. However, this approach is limiting for cellular particle tracking applications of DHPSF because of the heterogeneous signal background, high particle densities, and large variation in intensities of the target particles encountered in such experiments. Here, we present a data-driven and fast method based on deep learning (DL) to address these challenges. Specifically, we use the DL approach to analyze DHPSF data without the need to introduce heuristic fitting functions or interpolate calibration scans. We demonstrate the accuracy of the method on localizing simulated data in 3D, and test its efficacy in the presence of noisy, heterogeneous backgrounds. Finally, we localize and track in 3D puncta of human T-cell leukemia virus type 1 (HTLV-1) in live cells and present preliminary data on the mobilities of these particles measured in this noisy environment. This work has been supported by grants from the National Institutes of Health (R01 GM098550 and RO1 GM124279).

Mutations in the gene encoding dynamin 2 (DNM2), a GTPase that catalyzes membrane constriction and fission, are associated with two autosomal-dominant motor disorders, Charcot-Marie-Tooth disease (CMT) and centronuclear myopathy (CNM), which affect nerve and muscle, respectively. Many of these mutations affect the pleckstrin homology domain of DNM2, yet there is almost no overlap between the sets of mutations that cause CMT or CNM. A subset of CMT-linked mutations inhibit the interaction of DNM2 with phosphatidylinositol (4,5) bisphosphate, which is essential for DNM2 function in endocytosis. In contrast, CNM-linked mutations inhibit intramolecular interactions that normally suppress dynamin self-assembly and GTPase activation. Hence, CNM-linked DNM2 mutants form abnormally stable polymers and express enhanced assembly-dependent GTPase activation. These distinct effects of CMT and CNM mutations are consistent with current findings that DNM2-dependent CMT and CNM are loss-of-function and gain-of-function diseases, respectively. In this study, we present evidence that at least one CMT-causing DNM2 mutant (ΔDEE; lacking residues 555DEE557) forms polymers that, like the CNM mutants, are resistant to disassembly and display enhanced GTPase activation. We further show that the ΔDEE mutant undergoes 2-3-fold higher levels of tyrosine phosphorylation than wild-type DNM2. These results suggest that molecular mechanisms underlying the absence of pathogenic overlap between DNM2-dependent CMT and CNM should be re-examined.