A Type I Photosensitizer-Polymersome Boosts Reactive Oxygen Species Generation by Forcing H-Aggregation for Amplifying STING Immunotherapy.

Activation of the innate immune Stimulator of Interferon Genes (STING) pathway potentiates antitumor immunity. However, delivering STING agonists systemically to tumors presents a formidable challenge, and resistance to STING monotherapy has emerged in clinical trials with diminishing natural killer (NK) cell proliferation. Here, we encapsulated the STING agonist diABZI within polymersomes containing a Type I photosensitizer (NBS), creating a nanoagonist (PNBS/diABZI) for highly responsive tumor immunotherapy. This structure promoted H-aggregation and intersystem crossing of NBS, resulting in a ∼ 3-fold amplification in superoxide anion and singlet oxygen generation. The photodynamic therapy directly damaged hypoxia tumor cells and stimulated the proliferation of NK cells and cytotoxic T lymphocytes, thereby sensitizing STING immunotherapy. A single systemic intravenous administration of PNBS/diABZI eradicated orthotopic mammary tumors in murine models, achieving long-term antitumor immune memory to inhibit tumor recurrence and metastasis and significantly improving long-term tumor-free survival. This work provides a design rule for boosting reactive oxygen species production by promoting the intersystem crossing process, highlighting the potential of Type I photosensitizer-polymer vehicles for augmenting STING immunotherapy.

Altruistic feeding and cell-cell signaling during bacterial differentiation actively enhance phenotypic heterogeneity.

Starvation triggers bacterial spore formation, a committed differentiation program that transforms a vegetative cell into a dormant spore. Cells in a population enter sporulation nonuniformly to secure against the possibility that favorable growth conditions, which put sporulation-committed cells at a disadvantage, may resume. This heterogeneous behavior is initiated by a passive mechanism: stochastic activation of a master transcriptional regulator. Here, we identify a cell-cell communication pathway containing the proteins ShfA (YabQ) and ShfP (YvnB) that actively promotes phenotypic heterogeneity, wherein Bacillus subtilis cells that start sporulating early use a calcineurin-like phosphoesterase to release glycerol, which simultaneously acts as a signaling molecule and a nutrient to delay nonsporulating cells from entering sporulation. This produced a more diverse population that was better poised to exploit a sudden influx of nutrients compared to those generating heterogeneity via stochastic gene expression alone. Although conflict systems are prevalent among microbes, genetically encoded cooperative behavior in unicellular organisms can evidently also boost inclusive fitness.

Convolutional neural network transformer (CNNT) for fluorescence microscopy image denoising with improved generalization and fast adaptation.

Deep neural networks can improve the quality of fluorescence microscopy images. Previous methods, based on Convolutional Neural Networks (CNNs), require time-consuming training of individual models for each experiment, impairing their applicability and generalization. In this study, we propose a novel imaging-transformer based model, Convolutional Neural Network Transformer (CNNT), that outperforms CNN based networks for image denoising. We train a general CNNT based backbone model from pairwise high-low Signal-to-Noise Ratio (SNR) image volumes, gathered from a single type of fluorescence microscope, an instant Structured Illumination Microscope. Fast adaptation to new microscopes is achieved by fine-tuning the backbone on only 5-10 image volume pairs per new experiment. Results show that the CNNT backbone and fine-tuning scheme significantly reduces training time and improves image quality, outperforming models trained using only CNNs such as 3D-RCAN and Noise2Fast. We show three examples of efficacy of this approach in wide-field, two-photon, and confocal fluorescence microscopy.

Modulation of biophysical properties of nucleocapsid protein in the mutant spectrum of SARS-CoV-2.

Genetic diversity is a hallmark of RNA viruses and the basis for their evolutionary success. Taking advantage of the uniquely large genomic database of SARS-CoV-2, we examine the impact of mutations across the spectrum of viable amino acid sequences on the biophysical phenotypes of the highly expressed and multifunctional nucleocapsid protein. We find variation in the physicochemical parameters of its extended intrinsically disordered regions (IDRs) sufficient to allow local plasticity, but also observe functional constraints that similarly occur in related coronaviruses. In biophysical experiments with several N-protein species carrying mutations associated with major variants, we find that point mutations in the IDRs can have nonlocal impact and modulate thermodynamic stability, secondary structure, protein oligomeric state, particle formation, and liquid-liquid phase separation. In the Omicron variant, distant mutations in different IDRs have compensatory effects in shifting a delicate balance of interactions controlling protein assembly properties, and include the creation of a new protein-protein interaction interface in the N-terminal IDR through the defining P13L mutation. A picture emerges where genetic diversity is accompanied by significant variation in biophysical characteristics of functional N-protein species, in particular in the IDRs.

Like other types of RNA viruses, the genetic material of SARS-CoV-2 (the agent responsible for COVID-19) is formed of an RNA molecule which is prone to accumulating mutations. This gives SARS-CoV-2 the ability to evolve quickly, and often to remain one step ahead of treatments. Understanding how these mutations shape the behavior of RNA viruses is therefore crucial to keep diseases such as COVID-19 under control. The gene that codes for the protein that 'packages' the genetic information inside SARS-CoV-2 is particularly prone to mutations. This nucleocapsid (N) protein participates in many key processes during the life cycle of the virus, including potentially interfering with the immune response. Exactly how the physical properties of the N-Protein are impacted by the mutations in its genetic sequence remains unclear. To investigate this question, Nguyen et al. predicted the various biophysical properties of different regions of the N-protein based on a computer-based analysis of SARS-CoV-2 genetic databases. This allowed them to determine if specific protein regions were positively or negatively charged in different mutants. The analyses showed that some domains exhibited great variability in their charge between protein variants ­ reflecting the fact that the corresponding genetic sequences showed high levels of plasticity. Other regions remained conserved, however, including across related coronaviruses. Nguyen et al. also conducted biochemical experiments on a range of N-proteins obtained from clinically relevant SARS-CoV-2 variants. Their results highlighted the importance of protein segments with no fixed three-dimensional structure. Mutations in the related sequences created high levels of variation in the physical properties of these 'intrinsically disordered' regions, which had wide-ranging consequences. Some of these genetic changes even gave individual N-proteins the ability to interact with each other in a completely new way. These results shed new light on the relationship between genetic mutations and the variable physical properties of RNA virus proteins. Nguyen et al. hope that this knowledge will eventually help to develop more effective treatments for viral infections.

Altruistic feeding and cell-cell signaling during bacterial differentiation actively enhance phenotypic heterogeneity.

Starvation triggers bacterial spore formation, a committed differentiation program that transforms a vegetative cell into a dormant spore. Cells in a population enter sporulation non-uniformly to secure against the possibility that favorable growth conditions, which puts sporulation-committed cells at a disadvantage, may resume. This heterogeneous behavior is initiated by a passive mechanism: stochastic activation of a master transcriptional regulator. Here, we identify a cell-cell communication pathway that actively promotes phenotypic heterogeneity, wherein Bacillus subtilis cells that start sporulating early utilize a calcineurin-like phosphoesterase to release glycerol, which simultaneously acts as a signaling molecule and a nutrient to delay non-sporulating cells from entering sporulation. This produced a more diverse population that was better poised to exploit a sudden influx of nutrients compared to those generating heterogeneity via stochastic gene expression alone. Although conflict systems are prevalent among microbes, genetically encoded cooperative behavior in unicellular organisms can evidently also boost inclusive fitness.

Convolutional Neural Network Transformer (CNNT) for Fluorescence Microscopy image Denoising with Improved Generalization and Fast Adaptation.

Deep neural networks have been applied to improve the image quality of fluorescence microscopy imaging. Previous methods are based on convolutional neural networks (CNNs) which generally require more time-consuming training of separate models for each new imaging experiment, impairing the applicability and generalization. Once the model is trained (typically with tens to hundreds of image pairs) it can then be used to enhance new images that are like the training data. In this study, we proposed a novel imaging-transformer based model, Convolutional Neural Network Transformer (CNNT), to outperform the CNN networks for image denoising. In our scheme we have trained a single CNNT based "backbone model" from pairwise high-low SNR images for one type of fluorescence microscope (instance structured illumination, iSim). Fast adaption to new applications was achieved by fine-tuning the backbone on only 5-10 sample pairs per new experiment. Results show the CNNT backbone and fine-tuning scheme significantly reduces the training time and improves the image quality, outperformed training separate models using CNN approaches such as - RCAN and Noise2Fast. Here we show three examples of the efficacy of this approach on denoising wide-field, two-photon and confocal fluorescence data. In the confocal experiment, which is a 5×5 tiled acquisition, the fine-tuned CNNT model reduces the scan time form one hour to eight minutes, with improved quality.

Three-dimensional spatio-angular fluorescence microscopy with a polarized dual-view inverted selective-plane illumination microscope (pol-diSPIM).

Polarized fluorescence microscopy is a valuable tool for measuring molecular orientations, but techniques for recovering three-dimensional orientations and positions of fluorescent ensembles are limited. We report a polarized dual-view light-sheet system for determining the three-dimensional orientations and diffraction-limited positions of ensembles of fluorescent dipoles that label biological structures, and we share a set of visualization, histogram, and profiling tools for interpreting these positions and orientations. We model our samples, their excitation, and their detection using coarse-grained representations we call orientation distribution functions (ODFs). We apply ODFs to create physics-informed models of image formation with spatio-angular point-spread and transfer functions. We use theory and experiment to conclude that light-sheet tilting is a necessary part of our design for recovering all three-dimensional orientations. We use our system to extend known two-dimensional results to three dimensions in FM1-43-labelled giant unilamellar vesicles, fast-scarlet-labelled cellulose in xylem cells, and phalloidin-labelled actin in U2OS cells. Additionally, we observe phalloidin-labelled actin in mouse fibroblasts grown on grids of labelled nanowires and identify correlations between local actin alignment and global cell-scale orientation, indicating cellular coordination across length scales.

Cell division machinery drives cell-specific gene activation during differentiation in Bacillus subtilis.

When faced with starvation, the bacterium Bacillus subtilis transforms itself into a dormant cell type called a "spore". Sporulation initiates with an asymmetric division event, which requires the relocation of the core divisome components FtsA and FtsZ, after which the sigma factor σF is exclusively activated in the smaller daughter cell. Compartment-specific activation of σF requires the SpoIIE phosphatase, which displays a biased localization on one side of the asymmetric division septum and associates with the structural protein DivIVA, but the mechanism by which this preferential localization is achieved is unclear. Here, we isolated a variant of DivIVA that indiscriminately activates σF in both daughter cells due to promiscuous localization of SpoIIE, which was corrected by overproduction of FtsA and FtsZ. We propose that the core components of the redeployed cell division machinery drive the asymmetric localization of DivIVA and SpoIIE to trigger the initiation of the sporulation program.

Modulation of Biophysical Properties of Nucleocapsid Protein in the Mutant Spectrum of SARS-CoV-2.

Genetic diversity is a hallmark of RNA viruses and the basis for their evolutionary success. Taking advantage of the uniquely large genomic database of SARS-CoV-2, we examine the impact of mutations across the spectrum of viable amino acid sequences on the biophysical phenotypes of the highly expressed and multifunctional nucleocapsid protein. We find variation in the physicochemical parameters of its extended intrinsically disordered regions (IDRs) sufficient to allow local plasticity, but also exhibiting functional constraints that similarly occur in related coronaviruses. In biophysical experiments with several N-protein species carrying mutations associated with major variants, we find that point mutations in the IDRs can have nonlocal impact and modulate thermodynamic stability, secondary structure, protein oligomeric state, particle formation, and liquid-liquid phase separation. In the Omicron variant, distant mutations in different IDRs have compensatory effects in shifting a delicate balance of interactions controlling protein assembly properties, and include the creation of a new protein-protein interaction interface in the N-terminal IDR through the defining P13L mutation. A picture emerges where genetic diversity is accompanied by significant variation in biophysical characteristics of functional N-protein species, in particular in the IDRs.

Real-time imaging of drug-induced trapping of cellular topoisomerases and poly(ADP-ribose) polymerase 1 at the single-molecule level.

Topoisomerases (TOP1, TOP2α, and ß) are nuclear enzymes crucial for virtually all aspects of DNA metabolisms. They also are the targets of important anti-tumor chemotherapeutics that act by trapping the otherwise reversible topoisomerase-DNA covalent complex intermediates (TOPccs) that are formed during their catalytic reactions, resulting in long-lived topoisomerase DNA-protein crosslinks (TOP-DPCs) that interfere with DNA transactions. The Poly(ADP-ribose) polymerase (PARP) family protein PARP1 is activated by DNA damage to recruit DNA repair proteins, and PARP inhibitors are another class of commonly used chemotherapeutics, which bind and trap PARP molecules on DNA. To date, the trapping of TOPccs and PARP by their respective inhibitors can only be measured by immune-biochemical methods in cells. Here, we developed an imaging-based approach enabling real-time monitoring of drug-induced trapping of TOPccs and PARP1 in live cells at the single-molecule level. Capitalizing on this approach, we calculated the fraction of self-fluorescence tag-labeled topoisomerases and PARP single-molecules that are trapped by their respective inhibitors in real time. This novel technique should help elucidate the molecular processes that repair TOPcc and PARP trapping and facilitate the development of novel topoisomerase and PARP inhibitor-based therapies.

Dendritic distribution of autophagosomes underlies pathway-selective induction of LTD.

The mechanism of long-term depression (LTD), a cellular substrate for learning, memory, and behavioral flexibility, is extensively studied in Schaffer collateral (SC) synapses, with inhibition of autophagy identified as a key factor. SC inputs terminate at basal and proximal apical dendrites, whereas distal apical dendrites receive inputs from the temporoammonic pathway (TAP). Here, we demonstrate that TAP and SC synapses have a shared LTD mechanism reliant on NMDA receptors, caspase-3, and autophagy inhibition. Despite this shared LTD mechanism, proximal apical dendrites contain more autophagosomes than distal apical dendrites. Additionally, unlike SC LTD, which diminishes with age, TAP LTD persists into adulthood. Our previous study shows that the high autophagy in adulthood disallows SC LTD induction. The reduction of autophagosomes from proximal to distal dendrites, combined with distinct LTD inducibility at SC and TAP synapses, suggests a model where the differential distribution of autophagosomes in dendrites gates LTD inducibility at specific circuits.

Targeting neddylation sensitizes colorectal cancer to topoisomerase I inhibitors by inactivating the DCAF13-CRL4 ubiquitin ligase complex.

Colorectal cancers (CRCs) are prevalent worldwide, yet current treatments remain inadequate. Using chemical genetic screens, we identify that co-inhibition of topoisomerase I (TOP1) and NEDD8 is synergistically cytotoxic in human CRC cells. Combination of the TOP1 inhibitor irinotecan or its bioactive metabolite SN38 with the NEDD8-activating enzyme inhibitor pevonedistat exhibits synergy in CRC patient-derived organoids and xenografts. Mechanistically, we show that pevonedistat blocks the ubiquitin/proteasome-dependent repair of TOP1 DNA-protein crosslinks (TOP1-DPCs) induced by TOP1 inhibitors and that the CUL4-RBX1 complex (CRL4) is a prominent ubiquitin ligase acting on TOP1-DPCs for proteasomal degradation upon auto-NEDD8 modification during replication. We identify DCAF13, a DDB1 and Cullin Associated Factor, as the receptor of TOP1-DPCs for CRL4. Our study not only uncovers a replication-coupled ubiquitin-proteasome pathway for the repair of TOP1-DPCs but also provides molecular and translational rationale for combining TOP1 inhibitors and pevonedistat for CRC and other types of cancers.

Targeting N-linked Glycosylation for the Therapy of Aggressive Lymphomas.

Diffuse large B-cell lymphoma (DLBCL) can be subdivided into the activated B-cell (ABC) and germinal center B cell-like (GCB) subtypes. Self-antigen engagement of B-cell receptors (BCR) in ABC tumors induces their clustering, thereby initiating chronic active signaling and activation of NF-κB and PI3 kinase. Constitutive BCR signaling is essential in some GCB tumors but primarily activates PI3 kinase. We devised genome-wide CRISPR-Cas9 screens to identify regulators of IRF4, a direct transcriptional target of NF-κB and an indicator of proximal BCR signaling in ABC DLBCL. Unexpectedly, inactivation of N-linked protein glycosylation by the oligosaccharyltransferase-B (OST-B) complex reduced IRF4 expression. OST-B inhibition of BCR glycosylation reduced BCR clustering and internalization while promoting its association with CD22, which attenuated PI3 kinase and NF-κB activation. By directly interfering with proximal BCR signaling, OST-B inactivation killed models of ABC and GCB DLBCL, supporting the development of selective OST-B inhibitors for the treatment of these aggressive cancers. SIGNIFICANCE: DLBCL depends on constitutive BCR activation and signaling. There are currently no therapeutics that target the BCR directly and attenuate its pathologic signaling. Here, we unraveled a therapeutically exploitable, OST-B-dependent glycosylation pathway that drives BCR organization and proximal BCR signaling. This article is highlighted in the In This Issue feature, p. 1749.

A conserved oligomerization domain in the disordered linker of coronavirus nucleocapsid proteins.

The nucleocapsid (N-)protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has a key role in viral assembly and scaffolding of the viral RNA. It promotes liquid-liquid phase separation (LLPS), forming dense droplets that support the assembly of ribonucleoprotein particles with as-of-yet unknown macromolecular architecture. Combining biophysical experiments, molecular dynamics simulations, and analysis of the mutational landscape, we describe a heretofore unknown oligomerization site that contributes to LLPS, is required for the assembly of higher-order protein-nucleic acid complexes, and is coupled to large-scale conformational changes of N-protein upon nucleic acid binding. The self-association interface is located in a leucine-rich sequence of the intrinsically disordered linker between N-protein folded domains and formed by transient helices assembling into trimeric coiled-coils. Critical residues stabilizing hydrophobic and electrostatic interactions between adjacent helices are highly protected against mutations in viable SARS-CoV-2 genomes, and the oligomerization motif is conserved across related coronaviruses, thus presenting a target for antiviral therapeutics.

Three-dimensional structured illumination microscopy with enhanced axial resolution.

The axial resolution of three-dimensional structured illumination microscopy (3D SIM) is limited to ∼300 nm. Here we present two distinct, complementary methods to improve axial resolution in 3D SIM with minimal or no modification to the optical system. We show that placing a mirror directly opposite the sample enables four-beam interference with higher spatial frequency content than 3D SIM illumination, offering near-isotropic imaging with ∼120-nm lateral and 160-nm axial resolution. We also developed a deep learning method achieving ∼120-nm isotropic resolution. This method can be combined with denoising to facilitate volumetric imaging spanning dozens of timepoints. We demonstrate the potential of these advances by imaging a variety of cellular samples, delineating the nanoscale distribution of vimentin and microtubule filaments, observing the relative positions of caveolar coat proteins and lysosomal markers and visualizing cytoskeletal dynamics within T cells in the early stages of immune synapse formation.

Incorporating the image formation process into deep learning improves network performance.

We present Richardson-Lucy network (RLN), a fast and lightweight deep learning method for three-dimensional fluorescence microscopy deconvolution. RLN combines the traditional Richardson-Lucy iteration with a fully convolutional network structure, establishing a connection to the image formation process and thereby improving network performance. Containing only roughly 16,000 parameters, RLN enables four- to 50-fold faster processing than purely data-driven networks with many more parameters. By visual and quantitative analysis, we show that RLN provides better deconvolution, better generalizability and fewer artifacts than other networks, especially along the axial dimension. RLN outperforms classic Richardson-Lucy deconvolution on volumes contaminated with severe out of focus fluorescence or noise and provides four- to sixfold faster reconstructions of large, cleared-tissue datasets than classic multi-view pipelines. We demonstrate RLN's performance on cells, tissues and embryos imaged with widefield-, light-sheet-, confocal- and super-resolution microscopy.

Plasticity in structure and assembly of SARS-CoV-2 nucleocapsid protein.

Worldwide SARS-CoV-2 sequencing efforts track emerging mutations in its spike protein, as well as characteristic mutations in other viral proteins. Besides their epidemiological importance, the observed SARS-CoV-2 sequences present an ensemble of viable protein variants, and thereby a source of information on viral protein structure and function. Charting the mutational landscape of the nucleocapsid (N) protein that facilitates viral assembly, we observe variability exceeding that of the spike protein, with more than 86% of residues that can be substituted, on average by three to four different amino acids. However, mutations exhibit an uneven distribution that tracks known structural features but also reveals highly protected stretches of unknown function. One of these conserved regions is in the central disordered linker proximal to the N-G215C mutation that has become dominant in the Delta variant, outcompeting G215 variants without further spike or N-protein substitutions. Structural models suggest that the G215C mutation stabilizes conserved transient helices in the disordered linker serving as protein-protein interaction interfaces. Comparing Delta variant N-protein to its ancestral version in biophysical experiments, we find a significantly more compact and less disordered structure. N-G215C exhibits substantially stronger self-association, shifting the unliganded protein from a dimeric to a tetrameric oligomeric state, which leads to enhanced coassembly with nucleic acids. This suggests that the sequence variability of N-protein is mirrored by high plasticity of N-protein biophysical properties, which we hypothesize can be exploited by SARS-CoV-2 to achieve greater efficiency of viral assembly, and thereby enhanced infectivity.

[Analysis of Pollution Characteristics and Sources of Rainfall Runoff from Roofs in the Central District of Beijing].

The rainwater and rainfall runoff of roofs in the central district of Beijing from June to September in 2019 were sampled and analyzed to study the characteristics of the water quality, the first flush effect, and the main influential factors and sources of pollutants. The results showed that the roof runoff was seriously polluted by total nitrogen, ammonia nitrogen, chemical oxygen demand, and total suspended solids whose event mean concentration (EMC) exceeded the fifth level of environmental quality standards for surface water (GB 3838-2002) (the EMC of suspended solids exceeded the second level of discharge standard of pollutants for municipal wastewater treatment plants (GB 18918-2002)). The rainwater was relatively less polluted than the rainfall runoff, but the EMC of ammonia nitrogen and total nitrogen of the rainwater also exceeded the standard in some rainfall events. The first flush intensity of the rainfall runoffs was between weak and medium. The sequence of strength of the first flush of different pollutants was ammonia nitrogen>total suspended solids>chemical oxygen demand>total nitrogen>mercury>zinc>total phosphorus>lead. The concentration of total suspended solids, chemical oxygen demand, and total phosphorus in roof runoff were significantly positively correlated with the length of rainfall and the dry period and negatively correlated with the rainfall intensity. According to the results of principal component analysis, the main pollutant in rainwater was nitrogen emitted by vehicles, and the main pollutants in roof runoffs were suspended solids, organic matters, and phosphorus pollutants released from the aging of roofing materials and the corrosion of metal down pipes.

The HIV-1 Viral Protease Is Activated during Assembly and Budding Prior to Particle Release.

HIV-1 encodes a viral protease that is essential for the maturation of infectious viral particles. While protease inhibitors are effective antiretroviral agents, recent studies have shown that prematurely activating, rather than inhibiting, protease function leads to the pyroptotic death of infected cells, with exciting implications for efforts to eradicate viral reservoirs. Despite 40 years of research into the kinetics of protease activation, it remains unclear exactly when protease becomes activated. Recent reports have estimated that protease activation occurs minutes to hours after viral release, suggesting that premature protease activation is challenging to induce efficiently. Here, monitoring viral protease activity with sensitive techniques, including nanoscale flow cytometry and instant structured illumination microscopy, we demonstrate that the viral protease is activated within cells prior to the release of free virions. Using genetic mutants that lock protease into a precursor conformation, we further show that both the precursor and mature protease have rapid activation kinetics and that the activity of the precursor protease is sufficient for viral fusion with target cells. Our finding that HIV-1 protease is activated within producer cells prior to release of free virions helps resolve a long-standing question of when protease is activated and suggests that only a modest acceleration of protease activation kinetics is required to induce potent and specific elimination of HIV-infected cells. IMPORTANCE HIV-1 protease inhibitors have been a mainstay of antiretroviral therapy for more than 2 decades. Although antiretroviral therapy is effective at controlling HIV-1 replication, persistent reservoirs of latently infected cells quickly reestablish replication if therapy is halted. A promising new strategy to eradicate the latent reservoir involves prematurely activating the viral protease, which leads to the pyroptotic killing of infected cells. Here, we use highly sensitive techniques to examine the kinetics of protease activation during and shortly after particle formation. We found that protease is fully activated before virus is released from the cell membrane, which is hours earlier than recent estimates. Our findings help resolve a long-standing debate as to when the viral protease is initially activated during viral assembly and confirm that prematurely activating HIV-1 protease is a viable strategy to eradicate infected cells following latency reversal.

Plasticity in structure and assembly of SARS-CoV-2 nucleocapsid protein.

Worldwide SARS-CoV-2 sequencing efforts track emerging mutations in its spike protein, as well as characteristic mutations in other viral proteins. Besides their epidemiological importance, the observed SARS-CoV-2 sequences present an ensemble of viable protein variants, and thereby a source of information on viral protein structure and function. Charting the mutational landscape of the nucleocapsid (N) protein that facilitates viral assembly, we observe variability exceeding that of the spike protein, with more than 86% of residues that can be substituted, on average by 3-4 different amino acids. However, mutations exhibit an uneven distribution that tracks known structural features but also reveals highly protected stretches of unknown function. One of these conserved regions is in the central disordered linker proximal to the N-G215C mutation that has become dominant in the Delta variant, outcompeting G215 variants without further spike or N-protein substitutions. Structural models suggest that the G215C mutation stabilizes conserved transient helices in the disordered linker serving as protein-protein interaction interfaces. Comparing Delta variant N-protein to its ancestral version in biophysical experiments, we find a significantly more compact and less disordered structure. N-G215C exhibits substantially stronger self-association, shifting the unliganded protein from a dimeric to a tetrameric oligomeric state, which leads to enhanced co-assembly with nucleic acids. This suggests that the sequence variability of N-protein is mirrored by high plasticity of N-protein biophysical properties, which we hypothesize can be exploited by SARS-CoV-2 to achieve greater efficiency of viral assembly, and thereby enhanced infectivity.