Mass Photometry of Membrane Proteins

Integral membrane proteins (IMPs) are biologically highly significant but challenging to study because they require maintaining a cellular lipid-like environment. Here, we explore the application of mass photometry (MP) to IMPs and membrane-mimetic systems at the single-particle level. We apply MP to amphipathic vehicles, such as detergents and amphipols, as well as to lipid and native nanodiscs, characterizing the particle size, sample purity, and heterogeneity. Using methods established for cryogenic electron microscopy, we eliminate detergent background, enabling high-resolution studies of membrane-protein structure and interactions. We find evidence that, when extracted from native membranes using native styrene-maleic acid nanodiscs, the potassium channel KcsA is present as a dimer of tetramers—in contrast to results obtained using detergent purification. Finally, using lipid nanodiscs, we show that MP can help distinguish between functional and non-functional nanodisc assemblies, as well as determine the critical factors for lipid nanodisc formation

Mass Photometry of Membrane Proteins

Integral membrane proteins (IMPs) are biologically highly significant but challenging to study because they require maintaining a cellular lipid-like environment. Here, we explore the application of mass photometry (MP) to IMPs and membrane-mimetic systems at the single-particle level. We apply MP to amphipathic vehicles, such as detergents and amphipols, as well as to lipid and native nanodiscs, characterizing the particle size, sample purity, and heterogeneity. Using methods established for cryogenic electron microscopy, we eliminate detergent background, enabling high-resolution studies of membrane-protein structure and interactions. We find evidence that, when extracted from native membranes using native styrene-maleic acid nanodiscs, the potassium channel KcsA is present as a dimer of tetramers-in contrast to results obtained using detergent purification. Finally, using lipid nanodiscs, we show that MP can help distinguish between functional and non-functional nanodisc assemblies, as well as determine the critical factors for lipid nanodisc formation

Dosage-sensitive region causing locomotor dysfunction.

<p>Diagram on left shows Hsa21 indicating short and long arms separated by the centromere (oval), banding structure and length in Mb. The orthologous region of Mmu16 is indicated in grey and the regions of Mmu16 duplicated in Ts1Rhr, Dp4Tyb, Dp5Tyb and Dp6Tyb mouse models are indicated in black. On the right these duplicated regions are expanded and all known protein coding genes in these intervals and two microRNA genes (<i>Mir802</i> and <i>Gm23062</i>) are listed (mouse genome assembly GRCm38.p4). The locomotor defect assayed by Rotarod maps to a minimal interval resulting from the overlap of Ts1Rhr, Dp4Tyb and Dp5Tyb with genes in the interval indicated in blue. The <i>Dyrk1a</i> gene (bold) is required in 3 copies for the locomotor defect. Genes outside this region are listed in black.</p

Quantitative mass imaging of single biological macromolecules

The cellular processes underpinning life are orchestrated by proteins and their interactions. The associated structural and dynamic heterogeneity, despite being key to function, poses a fundamental challenge to existing analytical and structural methodologies. We used interferometric scattering microscopy to quantify the mass of single biomolecules in solution with 2% sequence mass accuracy, up to 19-kilodalton resolution, and 1-kilodalton precision. We resolved oligomeric distributions at high dynamic range, detected small-molecule binding, and mass-imaged proteins with associated lipids and sugars. These capabilities enabled us to characterize the molecular dynamics of processes as diverse as glycoprotein cross-linking, amyloidogenic protein aggregation, and actin polymerization. Interferometric scattering mass spectrometry allows spatiotemporally resolved measurement of a broad range of biomolecular interactions, one molecule at a time.</p

Increased <i>Dyrk1a</i> expression in Dp(16)1Yey and Dp3Tyb mice.

<p>(<b>a-d</b>) Mean±SEM mRNA levels of <i>Dyrk1a</i>, <i>Gad1</i> and <i>Gad2</i> in the cerebellum of Dp(16)1Yey mice at 10 weeks (<b>a</b>) and 6 days (<b>b</b>) of age and in 10 week old Dp3Tyb (<b>c</b>) and Dp5Tyb (<b>d</b>) mice. Expression of the test gene was normalized to <i>Gapdh</i> and then to expression in WT control mice (n = 5 of each genotype). Data analyzed with unpaired t-test, *p < 0.05, **p < 0.01, ***p < 0.001.</p

No broad defect in sensory behavior in Tc1 or Dp1Tyb mice.

<p>Analysis of Tc1 (<b>a</b>-<b>e</b>) and Dp1Tyb (<b>f-k</b>) mice at 14 weeks (<b>a-d</b>, <b>f-j</b>), or 11 weeks (<b>e,k</b>). (<b>a,f</b>) Withdrawal latency of right and left hind paws in response to cold plate. (<b>b,g</b>) Withdrawal latency of right and left hind paws in response to radiant heat (Hargreaves test). (<b>c,h</b>) Force required for 50% withdrawal of right and left hind paws in response to punctate mechanical stimulation (Von Frey test). (<b>d,i</b>) Number of nocifensive behaviors as a function of time following formalin injection into hind paw. (<b>e</b>,<b>k</b>) Quantification of sensory neuron subpopulations in dorsal root ganglia taken from L3-L5 region of (<b>e</b>) Tc1 mice and (<b>k</b>) Dp1Tyb mice showing the proportion of DRG cell profiles positive for the indicated markers. (<b>j</b>) Score representing ability of WT or Dp1Tyb mice to walk up a tapered inclined beam; a higher score indicates better performance. All graphs show mean±SEM (<b>a-d</b>, n = 10; <b>e</b>, n = 5; <b>f-j</b>, n = 7; <b>k</b>, n = 5). Data analyzed with unpaired t-test, *p < 0.05.</p

Locomotor dysfunction is caused by increased dosage of two short regions of Mmu16 including <i>Dyrk1a</i>.

<p>(<b>a</b>) Graphs show performance of 12-week old mice of the indicated genotypes on an accelerating Rotarod, showing the mean±SEM speed (rpm) at which they fell off, on three successive days of testing (n = 12 wild-type[WT], 14 Dp(16)1Yey; 11 WT, 12 Dp(17)1Yey; 11 WT, 17 Dp(10)1Yey; 6 WT, 5 Dp(16)1Yey, 6 Dp(16)1Yey/Dp(17)1Yey, 6 Dp(16)1Yey/Dp(10)1Yey, 10 Dp(17)1Yey/Dp(10)1Yey, 6 Dp(16)1Yey/Dp(17)1Yey/ Dp(10)1Yey; 13 WT, 15 Dp9Tyb; 9 WT, 12 Dp2Tyb; 9 WT, 18 Dp3Tyb; 15 WT, 15 Ts1Rhr; 15 WT, 15 Dp4Tyb; 15 WT, 20 Dp5Tyb; 15 WT, 15 Dp6Tyb; 36 WT, 18 Ts1Rhr, 21 Ts1Rhr/<i>Dyrk1a</i>^+/-; 10 WT, 5 Dp(16)1Yey, 10 Dp(16)1Yey/<i>Dyrk1a</i>^+/-). Data analyzed with 2-way ANOVA, *p < 0.05, **p < 0.01, ***p < 0.001; ns, not significant. (<b>b</b>) Mean±SEM number of foot errors made by 11-week old mice traversing a horizontal ladder in a Locotronic apparatus (n = 13 WT, 12 Dp1Tyb). Data analyzed with unpaired t-test, **p < 0.01.</p